Cerebral arterial pulsation drives paravascular CSF-interstitial fluid exchange in the murine brain.

PubMed

Iliff, Jeffrey J; Wang, Minghuan; Zeppenfeld, Douglas M; Venkataraman, Arun; Plog, Benjamin A; Liao, Yonghong; Deane, Rashid; Nedergaard, Maiken

2013-11-13

CSF from the subarachnoid space moves rapidly into the brain along paravascular routes surrounding penetrating cerebral arteries, exchanging with brain interstitial fluid (ISF) and facilitating the clearance of interstitial solutes, such as amyloid β, in a pathway that we have termed the "glymphatic" system. Prior reports have suggested that paravascular bulk flow of CSF or ISF may be driven by arterial pulsation. However, cerebral arterial pulsation could not be directly assessed. In the present study, we use in vivo two-photon microscopy in mice to visualize vascular wall pulsatility in penetrating intracortical arteries. We observed that unilateral ligation of the internal carotid artery significantly reduced arterial pulsatility by ~50%, while systemic administration of the adrenergic agonist dobutamine increased pulsatility of penetrating arteries by ~60%. When paravascular CSF-ISF exchange was evaluated in real time using in vivo two-photon and ex vivo fluorescence imaging, we observed that internal carotid artery ligation slowed the rate of paravascular CSF-ISF exchange, while dobutamine increased the rate of paravascular CSF-ISF exchange. These findings demonstrate that cerebral arterial pulsatility is a key driver of paravascular CSF influx into and through the brain parenchyma, and suggest that changes in arterial pulsatility may contribute to accumulation and deposition of toxic solutes, including amyloid β, in the aging brain.

The role of brain barriers in fluid movement in the CNS: is there a 'glymphatic' system?

PubMed

Abbott, N Joan; Pizzo, Michelle E; Preston, Jane E; Janigro, Damir; Thorne, Robert G

2018-03-01

Brain fluids are rigidly regulated to provide stable environments for neuronal function, e.g., low K + , Ca 2+ , and protein to optimise signalling and minimise neurotoxicity. At the same time, neuronal and astroglial waste must be promptly removed. The interstitial fluid (ISF) of the brain tissue and the cerebrospinal fluid (CSF) bathing the CNS are integral to this homeostasis and the idea of a glia-lymph or 'glymphatic' system for waste clearance from brain has developed over the last 5 years. This links bulk (convective) flow of CSF into brain along the outside of penetrating arteries, glia-mediated convective transport of fluid and solutes through the brain extracellular space (ECS) involving the aquaporin-4 (AQP4) water channel, and finally delivery of fluid to venules for clearance along peri-venous spaces. However, recent evidence favours important amendments to the 'glymphatic' hypothesis, particularly concerning the role of glia and transfer of solutes within the ECS. This review discusses studies which question the role of AQP4 in ISF flow and the lack of evidence for its ability to transport solutes; summarizes attributes of brain ECS that strongly favour the diffusion of small and large molecules without ISF flow; discusses work on hydraulic conductivity and the nature of the extracellular matrix which may impede fluid movement; and reconsiders the roles of the perivascular space (PVS) in CSF-ISF exchange and drainage. We also consider the extent to which CSF-ISF exchange is possible and desirable, the impact of neuropathology on fluid drainage, and why using CSF as a proxy measure of brain components or drug delivery is problematic. We propose that new work and key historical studies both support the concept of a perivascular fluid system, whereby CSF enters the brain via PVS convective flow or dispersion along larger caliber arteries/arterioles, diffusion predominantly regulates CSF/ISF exchange at the level of the neurovascular unit associated with CNS microvessels, and, finally, a mixture of CSF/ISF/waste products is normally cleared along the PVS of venules/veins as well as other pathways; such a system may or may not constitute a true 'circulation', but, at the least, suggests a comprehensive re-evaluation of the previously proposed 'glymphatic' concepts in favour of a new system better taking into account basic cerebrovascular physiology and fluid transport considerations.

Architectural setup for online monitoring and control of process parameters in robot-based ISF

NASA Astrophysics Data System (ADS)

Störkle, Denis Daniel; Thyssen, Lars; Kuhlenkötter, Bernd

2017-10-01

This article describes new developments in an incremental, robot-based sheet metal forming process (Roboforming) for the production of sheet metal components for small lot sizes and prototypes. The dieless kinematic-based generation of the shape is implemented by means of two industrial robots, which are interconnected to a cooperating robot system. Compared to other incremental sheet forming (ISF) machines, this system offers high geometrical design flexibility without the need of any part-dependent tools. However, the industrial application of ISF is still limited by certain constraints, e.g. the low geometrical accuracy. Responding to these constraints, the authors introduce a new architectural setup extending the current one by a superordinate process control. This sophisticated control consists of two modules, i.e. the compensation of the two industrial robots' low structural stiffness as well as a combined force/torque control. It is assumed that this contribution will lead to future research and development projects in which the authors will thoroughly investigate ISF process parameters influencing the geometric accuracy of the forming results.

Discrepancies Between Blood Glucose and Interstitial Glucose—Technological Artifacts or Physiology: Implications for Selection of the Appropriate Therapeutic Target

PubMed Central

Siegmund, Thorsten; Heinemann, Lutz; Kolassa, Ralf; Thomas, Andreas

2017-01-01

Background: For decades, the major source of information used to make therapeutic decisions by patients with diabetes has been glucose measurements using capillary blood samples. Knowledge gained from clinical studies, for example, on the impact of metabolic control on diabetes-related complications, is based on such measurements. Different to traditional blood glucose measurement systems, systems for continuous glucose monitoring (CGM) measure glucose in interstitial fluid (ISF). The assumption is that glucose levels in blood and ISF are practically the same and that the information provided can be used interchangeably. Thus, therapeutic decisions, that is, the selection of insulin doses, are based on CGM system results interpreted as though they were blood glucose values. Methods: We performed a more detailed analysis and interpretation of glucose profiles obtained with CGM in situations with high glucose dynamics to evaluate this potentially misleading assumption. Results: Considering physical activity, hypoglycemic episodes, and meal-related differences between glucose levels in blood and ISF uncover clinically relevant differences that can make it risky from a therapeutic point of view to use blood glucose for therapeutic decisions. Conclusions: Further systematic and structured evaluation as to whether the use of ISF glucose is more safe and efficient when it comes to acute therapeutic decisions is necessary. These data might also have a higher prognostic relevance when it comes to long-term metabolic consequences of diabetes. In the long run, it may be reasonable to abandon blood glucose measurements as the basis for diabetes management and switch to using ISF glucose as the appropriate therapeutic target. PMID:28322063

Validation of the Concurrent Atomistic-Continuum Method on Screw Dislocation/Stacking Fault Interactions

DOE PAGES

Xu, Shuozhi; Xiong, Liming; Chen, Youping; ...

2017-04-26

Dislocation/stacking fault interactions play an important role in the plastic deformation of metallic nanocrystals and polycrystals. These interactions have been explored in atomistic models, which are limited in scale length by high computational cost. In contrast, multiscale material modeling approaches have the potential to simulate the same systems at a fraction of the computational cost. In this paper, we validate the concurrent atomistic-continuum (CAC) method on the interactions between a lattice screw dislocation and a stacking fault (SF) in three face-centered cubic metallic materials—Ni, Al, and Ag. Two types of SFs are considered: intrinsic SF (ISF) and extrinsic SF (ESF).more » For the three materials at different strain levels, two screw dislocation/ISF interaction modes (annihilation of the ISF and transmission of the dislocation across the ISF) and three screw dislocation/ESF interaction modes (transformation of the ESF into a three-layer twin, transformation of the ESF into an ISF, and transmission of the dislocation across the ESF) are identified. Here, our results show that CAC is capable of accurately predicting the dislocation/SF interaction modes with greatly reduced DOFs compared to fully-resolved atomistic simulations.« less

Validation of the Concurrent Atomistic-Continuum Method on Screw Dislocation/Stacking Fault Interactions

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

Xu, Shuozhi; Xiong, Liming; Chen, Youping

Dislocation/stacking fault interactions play an important role in the plastic deformation of metallic nanocrystals and polycrystals. These interactions have been explored in atomistic models, which are limited in scale length by high computational cost. In contrast, multiscale material modeling approaches have the potential to simulate the same systems at a fraction of the computational cost. In this paper, we validate the concurrent atomistic-continuum (CAC) method on the interactions between a lattice screw dislocation and a stacking fault (SF) in three face-centered cubic metallic materials—Ni, Al, and Ag. Two types of SFs are considered: intrinsic SF (ISF) and extrinsic SF (ESF).more » For the three materials at different strain levels, two screw dislocation/ISF interaction modes (annihilation of the ISF and transmission of the dislocation across the ISF) and three screw dislocation/ESF interaction modes (transformation of the ESF into a three-layer twin, transformation of the ESF into an ISF, and transmission of the dislocation across the ESF) are identified. Here, our results show that CAC is capable of accurately predicting the dislocation/SF interaction modes with greatly reduced DOFs compared to fully-resolved atomistic simulations.« less

The Cancer Prevention and Control Research Network: An Interactive Systems Approach to Advancing Cancer Control Implementation Research and Practice

PubMed Central

Fernández, María E.; Melvin, Cathy L.; Leeman, Jennifer; Ribisl, Kurt M.; Allen, Jennifer D.; Kegler, Michelle C.; Bastani, Roshan; Ory, Marcia G.; Risendal, Betsy C.; Hannon, Peggy A.; Kreuter, Matthew W.; Hebert, James R.

2018-01-01

Background Although cancer research has advanced at a rapid pace, a gap remains between what is known about how to improve cancer prevention and control (CPC) and what is implemented as best practices within health care systems and communities. The Cancer Prevention and Control Research Network (CPCRN), with more than 10 years of dissemination and implementation research experience, aims to accelerate the uptake and use of evidence-based CPC interventions. Methods The collective work of the CPCRN has facilitated the analysis and categorization of research and implementation efforts according to the Interactive Systems Framework for Dissemination and Implementation (ISF), providing a useful heuristic for bridging the gap between prevention research and practice. The ISF authors have called for examples of its application as input to help refine the model. Results We provide examples of how the collaborative activities supported by the CPCRN, using community-engaged processes, accelerated the synthesis and translation of evidence, built both general and innovation-specific capacity, and worked with delivery systems to advance cancer control research and practice. Conclusions The work of the CPCRN has provided real-world examples of the application of the ISF and demonstrated that synthesizing and translating evidence can increase the potential that evidence-based CPC programs will be used and that capacity building for both the support system and the delivery system is crucial for the successful implementation and maintenance of evidence-based cancer control. Impact Adoption and implementation of CPC can be enhanced by better understanding ISF systems and intervening to improve them. PMID:25155759

Carprofen pharmacokinetics in plasma and in control and inflamed canine tissue fluid using in vivo ultrafiltration.

PubMed

Messenger, K M; Wofford, J A; Papich, M G

2016-02-01

Measurement of unbound drug concentrations at their sites of action is necessary for accurate PK/PD modeling. The objective of this study was to determine the unbound concentration of carprofen in canine interstitial fluid (ISF) using in vivo ultrafiltration and to compare pharmacokinetic parameters of free carprofen concentrations between inflamed and control tissue sites. We hypothesized that active concentrations of carprofen would exhibit different dispositions in ISF between inflamed vs. normal tissues. Bilateral ultrafiltration probes were placed subcutaneously in six healthy Beagle dogs 12 h prior to induction of inflammation. Two milliliters of either 2% carrageenan or saline control was injected subcutaneously at each probe site, 12 h prior to intravenous carprofen (4 mg/kg) administration. Plasma and ISF samples were collected at regular intervals for 72 h, and carprofen concentrations were determined using HPLC. Prostaglandin E2 (PGE2 ) concentrations were quantified in ISF using ELISA. Unbound carprofen concentrations were higher in ISF compared with predicted unbound plasma drug concentrations. Concentrations were not significantly higher in inflamed ISF compared with control ISF. Compartmental modeling was used to generate pharmacokinetic parameter estimates, which were not significantly different between sites. Terminal half-life (T½) was longer in the ISF compared with plasma. PGE2 in ISF decreased following administration of carprofen. In vivo ultrafiltration is a reliable method to determine unbound carprofen in ISF, and that disposition of unbound drug into tissue is much higher than predicted from unbound drug concentration in plasma. However, concentrations and pharmacokinetic parameter estimates are not significantly different in inflamed vs. un-inflamed tissues. © 2015 John Wiley & Sons Ltd.

Novel Functions of an Iron-Sulfur Flavoprotein from Trichomonas vaginalis Hydrogenosomes

PubMed Central

Smutná, Tamara; Pilarová, Katerina; Tarábek, Ján; Tachezy, Jan

2014-01-01

Iron-sulfur flavoproteins (Isf) are flavin mononucleotide (FMN)- and FeS cluster-containing proteins commonly encountered in anaerobic prokaryotes. However, with the exception of Isf from Methanosarcina thermophila, which participates in oxidative stress management by removing oxygen and hydrogen peroxide, none of these proteins has been characterized in terms of function. Trichomonas vaginalis, a sexually transmitted eukaryotic parasite of humans, was found to express several iron-sulfur flavoprotein (TvIsf) homologs in its hydrogenosomes. We show here that in addition to having oxygen-reducing activity, the recombinant TvIsf also functions as a detoxifying reductase of metronidazole and chloramphenicol, both of which are antibiotics effective against a variety of anaerobic microbes. TvIsf can utilize both NADH and reduced ferredoxin as electron donors. Given the prevalence of Isf in anaerobic prokaryotes, we propose that these proteins are central to a novel defense mechanism against xenobiotics. PMID:24663020

New directions in capacity building: incorporating cultural competence into the interactive systems framework.

PubMed

Gregory, Henry; Van Orden, Onna; Jordan, Lisa; Portnoy, Galina A; Welsh, Elena; Betkowski, Jennifer; Charles, Jade Wolfman; DiClemente, Carlo C

2012-12-01

The UMBC Psychology Department's Center for Community Collaboration (CCC) provides training and support for capacity building to promote substance abuse and mental health treatment as well as adherence improvement in community agencies funded through the Ryan White Act serving persons living with HIV/AIDS. This article describes an approach to dissemination of Evidence Based Practices (EBPs) for these services that uses the Interactive Systems Framework (ISF) and incorporates a collaborative process involving trainer cultural competence, along with a comprehensive assessment of organizational needs, culture, and climate that culminates in tailored training and ongoing collaboration. This article provides: (1) an overview of the CCC's expanded ISF for the effective dissemination of two EBPs-motivational interviewing and the stages of change perspective; (2) an examination of the role of trainer cultural competence within the ISF framework, particularly attending to organizational culture and climate; and (3) case examples to demonstrate this approach for both general and innovation-specific capacity building in two community based organizations.

Wearable physiological systems and technologies for metabolic monitoring.

PubMed

Gao, Wei; Brooks, George A; Klonoff, David C

2018-03-01

Wearable sensors allow continuous monitoring of metabolites for diabetes, sports medicine, exercise science, and physiology research. These sensors can continuously detect target analytes in skin interstitial fluid (ISF), tears, saliva, and sweat. In this review, we will summarize developments on wearable devices and their potential applications in research, clinical practice, and recreational and sporting activities. Sampling skin ISF can require insertion of a needle into the skin, whereas sweat, tears, and saliva can be sampled by devices worn outside the body. The most widely sampled metabolite from a wearable device is glucose in skin ISF for monitoring diabetes patients. Continuous ISF glucose monitoring allows estimation of the glucose concentration in blood without the pain, inconvenience, and blood waste of fingerstick capillary blood glucose testing. This tool is currently used by diabetes patients to provide information for dosing insulin and determining a diet and exercise plan. Similar technologies for measuring concentrations of other analytes in skin ISF could be used to monitor athletes, emergency responders, warfighters, and others in states of extreme physiological stress. Sweat is a potentially useful substrate for sampling analytes for metabolic monitoring during exercise. Lactate, sodium, potassium, and hydrogen ions can be measured in sweat. Tools for converting the concentrations of these analytes sampled from sweat, tears, and saliva into blood concentrations are being developed. As an understanding of the relationships between the concentrations of analytes in blood and easily sampled body fluid increases, then the benefits of new wearable devices for metabolic monitoring will also increase.

Exciton Correlations in Intramolecular Singlet Fission

DOE PAGES

Sanders, Samuel N.; Kumarasamy, Elango; Pun, Andrew B.; ...

2016-05-16

We have synthesized a series of asymmetric pentacene-tetracene heterodimers with a variable-length conjugated bridge that undergo fast and efficient intramolecular singlet fission (iSF). These compounds have distinct singlet and triplet energies, which allow us to study the spatial dynamics of excitons during the iSF process, including the significant role of exciton correlations in promoting triplet pair generation and recombination. We demonstrate that the primary photoexcitations in conjugated dimers are delocalized singlets that enable fast and efficient iSF. However, in these asymmetric dimers, the singlet becomes more localized on the lower energy unit as the length of the bridge is increased,more » slowing down iSF relative to analogous symmetric dimers. We resolve the recombination kinetics of the inequivalent triplets produced via iSF, and find that they primarily decay via concerted processes. By identifying different decay channels, including delayed fluorescence via triplet-triplet annihilation, we can separate transient species corresponding to both correlated triplet pairs and uncorrelated triplets. Recombination of the triplet pair proceeds rapidly despite our experimental and theoretical demonstration that individual triplets are highly localized and unable to be transported across the conjugated linker. In this class of compounds, the rate of formation and yield of uncorrelated triplets increases with bridge length. Overall, these constrained, asymmetric systems provide a unique platform to isolate and study transient species essential for singlet fission, which are otherwise difficult to observe in symmetric dimers or condensed phases.« less

Insect-Specific Flaviviruses: A Systematic Review of Their Discovery, Host Range, Mode of Transmission, Superinfection Exclusion Potential and Genomic Organization

PubMed Central

Blitvich, Bradley J.; Firth, Andrew E.

2015-01-01

There has been a dramatic increase in the number of insect-specific flaviviruses (ISFs) discovered in the last decade. Historically, these viruses have generated limited interest due to their inability to infect vertebrate cells. This viewpoint has changed in recent years because some ISFs have been shown to enhance or suppress the replication of medically important flaviviruses in co-infected mosquito cells. Additionally, comparative studies between ISFs and medically important flaviviruses can provide a unique perspective as to why some flaviviruses possess the ability to infect and cause devastating disease in humans while others do not. ISFs have been isolated exclusively from mosquitoes in nature but the detection of ISF-like sequences in sandflies and chironomids indicates that they may also infect other dipterans. ISFs can be divided into two distinct phylogenetic groups. The first group currently consists of approximately 12 viruses and includes cell fusing agent virus, Kamiti River virus and Culex flavivirus. These viruses are phylogenetically distinct from all other known flaviviruses. The second group, which is apparently not monophyletic, currently consists of nine viruses and includes Chaoyang virus, Nounané virus and Lammi virus. These viruses phylogenetically affiliate with mosquito/vertebrate flaviviruses despite their apparent insect-restricted phenotype. This article provides a review of the discovery, host range, mode of transmission, superinfection exclusion ability and genomic organization of ISFs. This article also attempts to clarify the ISF nomenclature because some of these viruses have been assigned more than one name due to their simultaneous discoveries by independent research groups. PMID:25866904

Research priorities of international sporting federations and the IOC research centres

PubMed Central

Talpey, Scott; Bradshaw, Ashley; Soligard, Torbjorn; Engebretsen, Lars

2016-01-01

Background/aim To be fully effective, the prevention of injury in sport and promotion of athlete's health needs to be both targeted and underpinned by scientific evidence. This study aimed to identify the research priorities of International Sporting Federation (ISFs) compared to the current research focus of the International Olympic Committee Research Centres (IOC-RCs). Methods Online survey of ISF Medical Chairpersons (n=22, 69% response) and IOC-RC Directors (n=7, 78% response). Open-ended responses relating to injury/illness priorities and specific athlete targets were thematically coded. Ratings were given of the need for different research types according to the Translating Research into Injury Prevention Practice (TRIPP) Framework stages. Results are presented as the frequency of ISFs and IOC-RCs separately. Results Both ISFs and IOC-RFs prioritised research into concussion (27%, 72%, respectively), competitive overuse (23%, 43%) and youth (41%, 43%). The ISFs also ranked catastrophic injuries (14%), environmental factors (18%), elite athletes (18%) and Paralympic athletes (14%) as important. The IOC-RCs gave higher priority to preventing respiratory illness (43%), long-term health consequences of injury (43%) and recreational athletes (43%). There was a trend towards ISFs valuing TRIPP stage 5/6 research more highly and for the IOC-RCs to value TRIPP stage 1/2 research. Conclusions There are clear opportunities to better link the priorities and actions of the ISFs and IOC-RCs, to ensure more effective practice-policy-research partnerships for the benefit of all athletes. Setting a mutually-agreed research agenda will require further active engagement between researchers and broader ISF representatives. PMID:27900197

Glucose metabolism disorder in obese children assessed by continuous glucose monitoring system.

PubMed

Zou, Chao-Chun; Liang, Li; Hong, Fang; Zhao, Zheng-Yan

2008-02-01

Continuous glucose monitoring system (CGMS) can measure glucose levels at 5-minute intervals over a few days, and may be used to detect hypoglycemia, guide insulin therapy, and control glucose levels. This study was undertaken to assess the glucose metabolism disorder by CGMS in obese children. Eighty-four obese children were studied. Interstitial fluid (ISF) glucose levels were measured by CGMS for 24 hours covering the time for oral glucose tolerance test (OGTT). Impaired glucose tolerance (IGT), impaired fasting glucose (IFG), type 2 diabetic mellitus (T2DM) and hypoglycemia were assessed by CGMS. Five children failed to complete CGMS test. The glucose levels in ISF measured by CGMS were highly correlated with those in capillary samples (r=0.775, P<0.001). However, the correlation between ISF and capillary glucose levels was lower during the first hour than that in the later time period (r=0.722 vs r=0.830), and the ISF glucose levels in 69.62% of children were higher than baseline levels in the initial 1-3 hours. In 79 obese children who finished the CGMS, 2 children had IFG, 2 had IGT, 3 had IFG + IGT, and 2 had T2DM. Nocturnal hypoglycemia was noted during the overnight fasting in 11 children (13.92%). Our data suggest that glucose metabolism disorder including hyperglycemia and hypoglycemia is very common in obese children. Further studies are required to improve the precision of the CGMS in children.

Ventricular dilation and electrical dyssynchrony synergistically increase regional mechanical nonuniformity but not mechanical dyssynchrony: a computational model.

PubMed

Kerckhoffs, Roy C P; Omens, Jeffrey H; McCulloch, Andrew D; Mulligan, Lawrence J

2010-07-01

Heart failure (HF) in combination with mechanical dyssynchrony is associated with a high mortality rate. To quantify contractile dysfunction in patients with HF, investigators have proposed several indices of mechanical dyssynchrony, including percentile range of time to peak shortening (WTpeak), circumferential uniformity ratio estimate (CURE), and internal stretch fraction (ISF). The goal of this study was to compare the sensitivity of these indices to 4 major abnormalities responsible for cardiac dysfunction in dyssynchronous HF: dilation, negative inotropy, negative lusitropy, and dyssynchronous activation. All combinations of these 4 major abnormalities were included in 3D computational models of ventricular electromechanics. Compared with a nonfailing heart model, ventricles were dilated, inotropy was reduced, twitch duration was prolonged, and activation sequence was changed from normal to left bundle branch block. In the nonfailing heart, CURE, ISF, and WTpeak were 0.97+/-0.004, 0.010+/-0.002, and 78+/-1 milliseconds, respectively. With dilation alone, CURE decreased 2.0+/-0.07%, ISF increased 58+/-47%, and WTpeak increased 31+/-3%. With dyssynchronous activation alone, CURE decreased 15+/-0.6%, ISF increased 14-fold (+/-3), and WTpeak increased 121+/-4%. With the combination of dilation and dyssynchronous activation, CURE decreased 23+/-0.8%, ISF increased 20-fold (+/-5), and WTpeak increased 147+/-5%. Dilation and left bundle branch block combined synergistically decreased regional cardiac function. CURE and ISF were sensitive to this combination, but WTpeak was not. CURE and ISF also reflected the relative nonuniform distribution of regional work better than WTpeak. These findings might explain why CURE and ISF are better predictors of reverse remodeling in cardiac resynchronization therapy.

The interactive systems framework applied to the strategic prevention framework: the Rhode Island experience.

PubMed

Florin, Paul; Friend, Karen B; Buka, Stephen; Egan, Crystelle; Barovier, Linda; Amodei, Brenda

2012-12-01

The Interactive Systems Framework for Dissemination and Implementation (ISF) was introduced as a heuristic systems level model to help bridge the gap between research and practice (Wandersman et al., in Am J Commun Psychol 41:171-181, 2008). This model describes three interacting systems with distinct functions that (1) distill knowledge to develop innovations; (2) provide supportive training and technical assistance for dissemination to; (3) a prevention delivery system responsible for implementation in the field. The Strategic Prevention Framework (SPF) is a major prevention innovation launched by the Center for Substance Abuse Prevention (CSAP) of the Substance Abuse and Mental Health Services Administration (SAMHSA). The SPF offers a structured, sequential, data-driven approach that explicitly targets environmental conditions in the community and aims for change in substance use and problems at the population level. This paper describes how the ISF was applied to the challenges of implementing the SPF in 14 Rhode Island communities, with a focus on the development of a new Training and Technical Assistance Resources Center to support SPF efforts. More specifically, we (1) describe each of the three ISF interacting systems as they evolved in Rhode Island; (2) articulate the lines of communication between the three systems; and (3) examine selected evaluation data to understand relationships between training and technical assistance and SPF implementation and outcomes.

Advanced Face Gear Surface Durability Evaluations

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Heath, Gregory F.

2016-01-01

The surface durability life of helical face gears and isotropic super-finished (ISF) face gears was investigated. Experimental fatigue tests were performed at the NASA Glenn Research Center. Endurance tests were performed on 10 sets of helical face gears in mesh with tapered involute helical pinions, and 10 sets of ISF-enhanced straight face gears in mesh with tapered involute spur pinions. The results were compared to previous tests on straight face gears. The life of the ISF configuration was slightly less than that of previous tests on straight face gears. The life of the ISF configuration was slightly greater than that of the helical configuration.

In situ fluidization for peat bed rupture, and preliminary economic analysis.

PubMed

Niven, R K; Khalili, N

2002-11-01

This study concerns in situ fluidization (ISF), a new remediation method with potential application to the remediation of NAPL and heavy metal contaminants, by their release from the fluidized zone generated by a water jet. The present study examines the effect of ISF on layers of peat, of significance owing to its role as an important NAPL and metal contaminant trap. Once trapped, such contaminants are not readily accessible by most remedial methods, due to the low permeability and diffusivity of the peat. A simple tank experiment is used to demonstrate rupture of a peat layer by ISF, with removal of the peat as elutriated fines and segregated peat chunks. The application of ISF in the field is then examined by three field trials in uncontaminated sands, in both saturated and unsaturated conditions. Fluidized depths of up to 1.9 m in the saturated zone (with refusal on a peat layer) and 2.5 m in the unsaturated zone (no refusal) were attained, using a 1.9-m-long, 50 mm diameter jet operated at 5-13 1 s(-1). Pulses of dark turbidity and shell fragments in the effluent indicated the rupture of peat and shelly layers. The experiments demonstrate the hydraulic viability of ISF in the field, and its ability to remove peat-based contaminants. The issues of appropriate jet design and water generation during ISF are discussed, followed by a preliminary economic analysis of ISF relative to existing remediation methods.

An Evaluation of the Biodiversity of Urban Ecology at ISF Academy

NASA Astrophysics Data System (ADS)

Ng, E.

2016-12-01

ISF Academy, a school with 1500 students in Hong Kong, is currently constructing two annex buildings, inside which are multiple green spaces. The biodiversity of plants at ISF Academy is currently limited, hence a selection of educationally meaningful native plant species are planned for the new buildings, with the goal of attracting butterflies, reducing the school's carbon footprint and creating biologically diverse spaces where students can study ecology. This project contains a biodiversity survey of existing plants in and around the ISF campus, and an evaluation of the plant selection for the annex buildings. While native species are planned for the buildings in order to ensure that the green spaces can be maintained sustainably, not all species are suitable for a school environment, and thus the safety, feasibility and ecological significance of the plant selection will be considered.As increasing amounts of people move towards cities, green spaces are necessary for alleviating climate change and for ensuring the sustainable development of urban environments. Despite being a small and densely populated city, more than 40% of Hong Kong's land mass consists of an extensive country park network. Hong Kong therefore serves as a prime example of how urban ecology can be implemented to benefit cities, and the green spaces in the ISF Academy campus can be considered a microcosm of urban ecology in Hong Kong. The implementation of green spaces in the ISF Academy campus demonstrates the ISF community's commitment to creating sustainable environments.

Preliminary Concept of Operations for the Spent Fuel Management System--WM2017

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

Cumberland, Riley M; Adeniyi, Abiodun Idowu; Howard, Rob L

The Nuclear Fuels Storage and Transportation Planning Project (NFST) within the U.S. Department of Energy s Office of Nuclear Energy is tasked with identifying, planning, and conducting activities to lay the groundwork for developing interim storage and transportation capabilities in support of an integrated waste management system. The system will provide interim storage for commercial spent nuclear fuel (SNF) from reactor sites and deliver it to a repository. The system will also include multiple subsystems, potentially including; one or more interim storage facilities (ISF); one or more repositories; facilities to package and/or repackage SNF; and transportation systems. The project teammore » is analyzing options for an integrated waste management system. To support analysis, the project team has developed a Concept of Operations document that describes both the potential integrated system and inter-dependencies between system components. The goal of this work is to aid systems analysts in the development of consistent models across the project, which involves multiple investigators. The Concept of Operations document will be updated periodically as new developments emerge. At a high level, SNF is expected to travel from reactors to a repository. SNF is first unloaded from reactors and placed in spent fuel pools for wet storage at utility sites. After the SNF has cooled enough to satisfy loading limits, it is placed in a container at reactor sites for storage and/or transportation. After transportation requirements are met, the SNF is transported to an ISF to store the SNF until a repository is developed or directly to a repository if available. While the high level operation of the system is straightforward, analysts must evaluate numerous alternative options. Alternative options include the number of ISFs (if any), ISF design, the stage at which SNF repackaging occurs (if any), repackaging technology, the types of containers used, repository design, component sizing, and timing of events. These alternative options arise due to technological, economic, or policy considerations. As new developments regularly emerge, the operational concepts will be periodically updated. This paper gives an overview of the different potential alternatives identified in the Concept of Operations document at a conceptual level.« less

Homeostasis and the concept of 'interstitial fluids hierarchy': Relevance of cerebrospinal fluid sodium concentrations and brain temperature control (Review).

PubMed

Agnati, Luigi F; Marcoli, Manuela; Leo, Giuseppina; Maura, Guido; Guidolin, Diego

2017-03-01

In this review, the aspects and further developments of the concept of homeostasis are discussed also in the perspective of their possible impact in the clinical practice, particularly as far as psychic homeostasis is concerned. A brief historical survey and comments on the concept of homeostasis and allostasis are presented to introduce our proposal that is based on the classical assumption of the interstitial fluid (ISF) as the internal medium for multicellular organisms. However, the new concept of a hierarchic role of ISF of the various organs is introduced. Additionally, it is suggested that particularly for some chemico‑physical parameters, oscillatory rhythms within their proper set‑ranges should be considered a fundamental component of homeostasis. Against this background, we propose that the brain ISF has the highest hierarchic role in human beings, providing the optimal environment, not simply for brain cell survival, but also for brain complex functions and the oscillatory rhythms of some parameters, such as cerebrospinal fluid sodium and brain ISF pressure waves, which may play a crucial role in brain physio‑pathological states. Thus, according to this proposal, the brain ISF represents the real internal medium since the maintenance of its dynamic intra-set-range homeostasis is the main factor for a free and independent life of higher vertebrates. Furthermore, the evolutionary links between brain and kidney and their synergistic role in H2O/Na balance and brain temperature control are discussed. Finally, it is surmised that these two interrelated parameters have deep effects on the Central Nervous System (CNS) higher integrative actions such those linked to psychic homeostasis.

Homeostasis and the concept of 'interstitial fluids hierarchy': Relevance of cerebrospinal fluid sodium concentrations and brain temperature control (Review)

PubMed Central

Agnati, Luigi F.; Marcoli, Manuela; Leo, Giuseppina; Maura, Guido; Guidolin, Diego

2017-01-01

In this review, the aspects and further developments of the concept of homeostasis are discussed also in the perspective of their possible impact in the clinical practice, particularly as far as psychic homeostasis is concerned. A brief historical survey and comments on the concept of homeostasis and allostasis are presented to introduce our proposal that is based on the classical assumption of the interstitial fluid (ISF) as the internal medium for multicellular organisms. However, the new concept of a hierarchic role of ISF of the various organs is introduced. Additionally, it is suggested that particularly for some chemico-physical parameters, oscillatory rhythms within their proper set-ranges should be considered a fundamental component of homeostasis. Against this background, we propose that the brain ISF has the highest hierarchic role in human beings, providing the optimal environment, not simply for brain cell survival, but also for brain complex functions and the oscillatory rhythms of some parameters, such as cerebrospinal fluid sodium and brain ISF pressure waves, which may play a crucial role in brain physio-pathological states. Thus, according to this proposal, the brain ISF represents the real internal medium since the maintenance of its dynamic intra-set-range homeostasis is the main factor for a free and independent life of higher vertebrates. Furthermore, the evolutionary links between brain and kidney and their synergistic role in H2O/Na balance and brain temperature control are discussed. Finally, it is surmised that these two interrelated parameters have deep effects on the Central Nervous System (CNS) higher integrative actions such those linked to psychic homeostasis. PMID:28204813

Favourable Outcomes of Endovascular Total Aortic Arch Repair Via Needle Based In Situ Fenestration at a Mean Follow-Up of 5.4 Months.

PubMed

Shang, Tao; Tian, Lu; Li, Dong-Lin; Wu, Zi-Heng; Zhang, Hong-Kun

2018-03-01

Endovascular repair of aortic arch pathologies remains challenging. Recently, needle based in situ fenestration (ISF) has shown great potential in endovascular total aortic arch repair (ETAAR). This study aimed to evaluate the feasibility, effectiveness, and safety of ETAAR via needle based ISF, and to present initial experience with this technique. Patients who met the inclusion criteria were enrolled in this prospective study. The supra-arch branches were manually punctured in a retrograde manner using liver biopsy needles (18 gauge/30 cm) in the left common carotid artery (LCCA) and brachiocephalic trunk (BCT), and endo-puncture system or aspiration biopsy needles (21-gauge) in the left subclavian artery (LSA). All the branches were revascularised with bridge stents. Routine follow-up occurred at 1, 3, 6, and 12 months post surgery. Ten patients with arch pathologies underwent ETAAR. Revascularisation of three branches was successfully performed in eight patients, but attempts to create ISF in LSA were unsuccessful in two patients because of tortuosity and sharp angle. The time taken to establish ISF in LCCA and BCT was 100.4s and 489.6s, respectively. Bilateral regional cerebral oxygen saturation (RCOS) decreased after the arch endograft deployment (both, p < .001) and recovered to the pre-operative level once both carotid arteries were reconstructed (left, p = .0856; right, p = .6). The right RCOS was higher with the beneficial effect of extracorporeal circulation (after cTAGs deployment, p < .001; after LCCA revascularised, p = .0148) during the ischaemic period. In one case, the left iliac artery ruptured, but no ISF related or neurological complications occurred. An early follow-up (mean 5.44 months) CTA and ultrasound confirmed patency of all the branch grafts without any endoleak or migration CONCLUSIONS: This study demonstrated that ETAAR via needle based ISF, making full use of off the shelf devices and techniques, can be successfully performed in aortic arch pathologies with a favourable early outcome. Copyright © 2017 European Society for Vascular Surgery. Published by Elsevier B.V. All rights reserved.

ICESat Science Investigator led Processing System (I-SIPS)

NASA Astrophysics Data System (ADS)

Bhardwaj, S.; Bay, J.; Brenner, A.; Dimarzio, J.; Hancock, D.; Sherman, M.

2003-12-01

The ICESat Science Investigator-led Processing System (I-SIPS) generates the GLAS standard data products. It consists of two main parts the Scheduling and Data Management System (SDMS) and the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software. The system has been operational since the successful launch of ICESat. It ingests data from the GLAS instrument, generates GLAS data products, and distributes them to the GLAS Science Computing Facility (SCF), the Instrument Support Facility (ISF) and the National Snow and Ice Data Center (NSIDC) ECS DAAC. The SDMS is the Planning, Scheduling and Data Management System that runs the GLAS Science Algorithm Software (GSAS). GSAS is based on the Algorithm Theoretical Basis Documents provided by the Science Team and is developed independently of SDMS. The SDMS provides the processing environment to plan jobs based on existing data, control job flow, data distribution, and archiving. The SDMS design is based on a mission-independent architecture that imposes few constraints on the science code thereby facilitating I-SIPS integration. I-SIPS currently works in an autonomous manner to ingest GLAS instrument data, distribute this data to the ISF, run the science processing algorithms to produce the GLAS standard products, reprocess data when new versions of science algorithms are released, and distributes the products to the SCF, ISF, and NSIDC. I-SIPS has a proven performance record, delivering the data to the SCF within hours after the initial instrument activation. The I-SIPS design philosophy gives this system a high potential for reuse in other science missions.

Sustainability Infused Curriculum

NASA Astrophysics Data System (ADS)

Ibarra, D. L.

2015-12-01

The Independent Schools Foundation Academy (ISF) in Hong Kong established a sustainability policy in 2015, which explicitly states, "an experimentally integrated, environmentally and ethically sustainable system of science education and conservation practices based on the 2012 Jeju Declaration of the World Conservation Congress will be implemented through the school". ISF Academy is a private Chinese bilingual school in Hong Kong serving over 1500 students K-12, following the framework and curriculum of the International Baccalaureate Organization (IBO). The strategy behind the implementation of this policy includes: development of a scientific sustainable curriculum that is age appropriate; establish a culture of sustainability within the ISF community and beyond to the wider HK community; install sustainable infrastructure that allows students to learn; and learn first hand sustainable living practices. It is well understood that solutions to the environmental challenges facing Hong Kong and our planet will require multiple disciplines. The current sustainability programs at ISF include: a) a whole school aerobic food waste composting system and organic farming, b) energy consumption monitoring of existing buildings, c) upcoming installation of an air pollution monitoring equipment that will correlate with the AQHI data collected by the Hong Kong government, d) a Renewable Energy Education Center (REEC) that will teach students about RE and also produce solar energy for classroom consumption, and e) student lead environmental group that manages the paper and used cooking oil recycling on campus. The Shuyuan Science and Sustainability faculty work closely with classroom teachers to ensure that the above mentioned projects are incorporated into the curriculum throughout the school. Interdisciplinary units (IDU) of study are being developed that encourage faculty and students to work across subject areas. Projects include Personal Projects, Extended Essays, bilingual organic farming for primary school students, and opportunities for students to work with outside researchers. There are also specific enrichment courses taught: green chemistry, earth systems, sustainability in a changing world, and natural water systems. Since 2013, senior students have presented at AGU Fall Meetings.

Investigations of Beam Dynamics Issues at Current and Future Hadron Accelerators

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

Ellison, James; Lau, Stephen; Heinemann, Klaus

Final Report Abstract for DE-FG02-99ER4110, May 15, 2011- October 15, 2014 There is a synergy between the fields of Beam Dynamics (BD) in modern particle accelerators and Applied Mathematics (AMa). We have formulated significant problems in BD and have developed and applied tools within the contexts of dynamical systems, topological methods, numerical analysis and scientific computing, probability and stochastic processes, and mathematical statistics. We summarize the three main areas of our AMa work since 2011. First, we continued our study of Vlasov-Maxwell systems. Previously, we developed a state of the art algorithm and code (VM3@A) to calculate coherent synchrotron radiationmore » in single pass systems. In this cycle we carefully analyzed the major expense, namely the integral-over-history (IOH), and developed two approaches to speed up integration. The first strategy uses a representation of the Bessel function J0 in terms of exponentials. The second relies on “local sequences” developed recently for radiation boundary conditions, which are used to reduce computational domains. Although motivated by practicality, both strategies involve interesting and rather deep analysis and approximation theory. As an alternative to VM3@A, we are integrating Maxwell’s equations by a time-stepping method, bypass- ing the IOH, using a Discontinuous Galerkin (DG) method. DG is a generalization of Finite Element and Finite Volume methods. It is spectrally convergent, unlike the commonly used Finite Difference methods, and can handle complicated vacuum chamber geometries. We have applied this in several contexts and have obtained very nice results including an explanation of an experiment at the Canadian Light Source, where the geometry is quite complex. Second, we continued our study of spin dynamics in storage rings. There is much current and proposed activity where spin polarized beams are being used in testing the Standard Model and its modifications. Our work has focused on invariant spin fields (ISFs) and amplitude dependent spin tunes (ADSTs), which are essential for estimating beam polarization. Several algorithms have been developed since the 1980s for computing the ISF, among them the Heinemann- Hoffstaetter method of stroboscopic averaging (SA) which is implemented in the code SPRINT. SA, which computes the ISF by using spin tracking data, can find the ISF to computer precision if it exists and thus can give evidence for existence of the ISF. Central to our work is resolving the ISF conjecture, which says that, off orbital resonance, an ISF exists. Thus Heinemann developed, in his 2010 PhD thesis, a new framework which unifies and generalizes the notions of ISF and ADST by using bundle theory. This lead to a long paper which was a major collaborative effort during the recent cycle. In a nutshell, our bundle approach elegantly unifies the dynamics of spin-1/2 and spin-1 particles, e.g., protons and deuterons. In fact it is well known that these two kinds of dynamics are driven by the same spin transfer matrix and in our approach one sees the deeper reason for this: the spin transfer matrix carries the natural dynamics of a principal bundle whereas the difference between the spin-1/2 and spin-1 dynamics lies in their different geometrical situation, i.e., different underlying associated bundles. Thus one arrives at new results for polarized beams, among them the Invariant Reduction Theorem (IRT) and the Cross Section Theorem (CST). The IRT gives a necessary and sufficient condition for the ISF to exist. The SA technique revealed, 20 years ago, that each ISF can be viewed as a complex agglomerate of spin tracking data. The bundle approach goes one step further by using the IRT and the CST to glue spin tracking data into agglomerates which are candidates for ISFs. We gain insight because the “good” agglomerates, in the presence of an ISF, are very different from the “bad” ones. Finally we mention that the bundle approach has analogies to the approach used in geometrical Yang-Mills theory. Third, we studied X-Ray Free Electron Lasers (FELs), which are electron accelerators producing coherent undulator radiation over a wide range of frequencies from microwaves to x-rays. The photon beams produced in FEL undulators are used to study material samples in biology, material science etc. We developed a mathematical analysis, based on the 6D Lorentz system, of energetic electrons moving through a planar undulator excited by a Maxwell traveling wave field of wavelength λ. Our Method of Averaging perturbation analysis yields non-resonant and near-to-resonant normal form approximations as a function of λ, which we present in two averaging theorems. We prove the theorems in detail, error bounds and giving a tutorial on mathematically rigorous perturbation theory in a context where proofs are easily understood. To our knowledge the planar problem has not been analyzed with the generality here nor has the standard FEL pendulum system, which appears on resonance, been derived with error bounds. In addition to the domains of validity of the normal forms we obtain new insights that require further study, including a more general low gain theory. With a firm foundation in the non-collective case above we are studying the 3D collective case from start up from noise to high gain and saturation. We have formulated the noise start up as a problem of going from the microscopic Klimontovich-Maxwell to the macroscopic Vlasov-Maxwell with a Vlasov correction term. In the 1D setting, we seek an alternative to the phenomenological Vlasov approach which models shot noise by a perturbation on an initial “smooth” density. The 1D wave equation with a Klimontovich source is often the starting point for the 1D FEL high gain theory. We have a new representation of solutions which may lead to new insights.« less

Proteomic Characterization of Dermal Interstitial Fluid Extracted Using a Novel Microneedle-Assisted Technique.

PubMed

Tran, Bao Quoc; Miller, Philip R; Taylor, Robert M; Boyd, Gabrielle; Mach, Phillip M; Rosenzweig, C Nicole; Baca, Justin T; Polsky, Ronen; Glaros, Trevor

2018-01-05

As wearable fitness devices have gained commercial acceptance, interest in real-time monitoring of an individual's physiological status using noninvasive techniques has grown. Microneedles have been proposed as a minimally invasive technique for sampling the dermal interstitial fluid (ISF) for clinical monitoring and diagnosis, but little is known about its composition. In this study, a novel microneedle array was used to collect dermal ISF from three healthy human donors and compared with matching serum and plasma samples. Using a shotgun quantitative proteomic approach, 407 proteins were quantified with at least one unique peptide, and of those, 135 proteins were differently expressed at least 2-fold. Collectively, these proteins tended to originate from the cytoplasm, membrane bound vesicles, and extracellular vesicular exosomes. Proteomic analysis confirmed previously published work that indicates that ISF is highly similar to both plasma and serum. In this study, less than one percent of proteins were uniquely identified in ISF. Taken together, ISF could serve as a minimally invasive alternative for blood-derived fluids with potential for real-time monitoring applications.

Bone tissue engineering: the role of interstitial fluid flow

NASA Technical Reports Server (NTRS)

Hillsley, M. V.; Frangos, J. A.

1994-01-01

It is well established that vascularization is required for effective bone healing. This implies that blood flow and interstitial fluid (ISF) flow are required for healing and maintenance of bone. The fact that changes in bone blood flow and ISF flow are associated with changes in bone remodeling and formation support this theory. ISF flow in bone results from transcortical pressure gradients produced by vascular and hydrostatic pressure, and mechanical loading. Conditions observed to alter flow rates include increases in venous pressure in hypertension, fluid shifts occurring in bedrest and microgravity, increases in vascularization during the injury-healing response, and mechanical compression and bending of bone during exercise. These conditions also induce changes in bone remodeling. Previously, we hypothesized that interstitial fluid flow in bone, and in particular fluid shear stress, serves to mediate signal transduction in mechanical loading- and injury-induced remodeling. In addition, we proposed that a lack or decrease of ISF flow results in the bone loss observed in disuse and microgravity. The purpose of this article is to review ISF flow in bone and its role in osteogenesis.

The Glymphatic System in Central Nervous System Health and Disease: Past, Present, and Future.

PubMed

Plog, Benjamin A; Nedergaard, Maiken

2018-01-24

The central nervous system (CNS) is unique in being the only organ system lacking lymphatic vessels to assist in the removal of interstitial metabolic waste products. Recent work has led to the discovery of the glymphatic system, a glial-dependent perivascular network that subserves a pseudolymphatic function in the brain. Within the glymphatic pathway, cerebrospinal fluid (CSF) enters the brain via periarterial spaces, passes into the interstitium via perivascular astrocytic aquaporin-4, and then drives the perivenous drainage of interstitial fluid (ISF) and its solute. Here, we review the role of the glymphatic pathway in CNS physiology, the factors known to regulate glymphatic flow, and the pathologic processes in which a breakdown of glymphatic CSF-ISF exchange has been implicated in disease initiation and progression. Important areas of future research, including manipulation of glymphatic activity aiming to improve waste clearance and therapeutic agent delivery, are also discussed.

Interstitial fluid glucose dynamics during insulin-induced hypoglycaemia.

PubMed

Steil, G M; Rebrin, K; Hariri, F; Jinagonda, S; Tadros, S; Darwin, C; Saad, M F

2005-09-01

Glucose sensors often measure s.c. interstitial fluid (ISF) glucose rather than blood or plasma glucose. Putative differences between plasma and ISF glucose include a protracted delay during the recovery from hypoglycaemia and an increased gradient during hyperinsulinaemia. These have often been investigated using sensor systems that have delays due to signal smoothing, or require long equilibration times. The aim of the present study was to define these relationships during hypoglycaemia in a well-equilibrated system with no smoothing. Hypoglycaemia was induced by i.v. insulin infusion (360 pmol.m(-2).min(-1)) in ten non-diabetic subjects. Glucose was sequentially clamped at approximately 5, 4.2 and 3.1 mmol/l and allowed to return to normoglycaemia. Subjects wore two s.c. glucose sensors (Medtronic MiniMed, Northridge, CA, USA) that had been inserted for more than 12 h. A two-compartment model was used to quantify the delay and gradient. The delay during the fall in plasma glucose was not different from the delay during recovery (8.3+/-0.67 vs 6.3+/-1.1 min; p=0.27) and no differences were observed in the ratio of sensor current to plasma glucose at basal insulin (2.7+/-0.25 nA.mmol(-1).l) compared with any of the hyperinsulinaemic clamp phases (2.8+/-0.18, 2.7+/-0.021, 2.9+/-0.21; p=NS). The ratio was significantly elevated following recovery to normoglycaemia (3.1+/-0.2 nA.mmol(-1).l; p<0.001). The elevated ratio suggests that the plasma to ISF glucose gradient was decreased following hypoglycaemia, possibly due to increased skin blood flow. Recovery from hypoglycaemia is not accompanied by a protracted delay and insulin does not increase the plasma to s.c. ISF glucose gradient.

The glymphatic system in CNS health and disease: past, present and future

PubMed Central

Plog, Benjamin A.; Nedergaard, Maiken

2018-01-01

The central nervous system (CNS) is unique in being the only organ system lacking lymphatic vessels to assist in the removal of interstitial metabolic waste products. Recent work has led to the discovery of the glymphatic system, a glial-dependent perivascular network that subserves a pseudo-lymphatic function in the brain. Within the glymphatic pathway, cerebrospinal fluid (CSF) enters brain via periarterial spaces, passes into the interstitium via perivascular astrocytic aquaporin-4, and then drives the perivenous drainage of interstitial fluid (ISF) and its solute. Here we review the role of the glymphatic pathway in CNS physiology, factors known to regulate glymphatic flow, and pathologic processes where a breakdown of glymphatic CSF-ISF exchange has been implicated in disease initiation and progression. Important areas of future research, including manipulation of glymphatic activity aiming to improve waste clearance and therapeutic agent delivery, will also be discussed. PMID:29195051

Volume transmission-mediated encephalopathies: a possible new concept?

PubMed

Hartung, Hans-Peter; Dihné, Marcel

2012-03-01

There is strong evidence that the composition of cerebrospinal fluid (CSF) influences brain development, neurogenesis, and behavior. The bidirectional exchange of CSF and interstitial fluid (ISF) across the ependymal and pia-glial membranes is required for these phenomena to occur. Because ISF surrounds the parenchymal compartment, neuroactive substances in the CSF and ISF can influence neuronal activity. Functionally important neuroactive substances are distributed to distant sites of the central nervous system by the convection and diffusion of CSF and ISF, a process known as volume transmission. It has recently been shown that pathologically altered CSF from patients with acute traumatic brain injury suppresses in vitro neuronal network activity (ivNNA) recorded by multielectrode arrays measuring synchronously bursting neural populations. Functionally relevant substances in pathologically altered CSF have been biochemically identified, and ivNNA has been partially recovered by pharmacologic intervention. It remains unclear whether the in vivo parenchymal compartment remains unaffected by pathologically altered CSF that significantly impairs ivNNA. We hypothesize that pathologic CSF alterations are not just passive indicators of brain diseases but that they actively and directly evoke functional disturbances in global brain activity through the distribution of neuroactive substances, for instance, secondary to focal neurologic disease. For this mechanism, we propose the new term volume transmission-mediated encephalopathies (VTE). Recording ivNNA in the presence of pure human CSF could help to identify and monitor functionally relevant CSF alterations that directly result in VTEs, and the collected data might point to therapeutic ways to antagonize these alterations.

SU-F-T-143: Implementation of a Correction-Based Output Model for a Compact Passively Scattered Proton Therapy System

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

Ferguson, S; Ahmad, S; Chen, Y

2016-06-15

Purpose: To commission and investigate the accuracy of an output (cGy/MU) prediction model for a compact passively scattered proton therapy system. Methods: A previously published output prediction model (Sahoo et al, Med Phys, 35, 5088–5097, 2008) was commissioned for our Mevion S250 proton therapy system. This model is a correction-based model that multiplies correction factors (d/MUwnc=ROFxSOBPF xRSFxSOBPOCFxOCRxFSFxISF). These factors accounted for changes in output due to options (12 large, 5 deep, and 7 small), modulation width M, range R, off-center, off-axis, field-size, and off-isocenter. In this study, the model was modified to ROFxSOBPFxRSFxOCRxFSFxISF-OCFxGACF by merging SOBPOCF and ISF for simplicitymore » and introducing a gantry angle correction factor (GACF). To commission the model, outputs over 1,000 data points were taken at the time of the system commissioning. The output was predicted by interpolation (1D for SOBPF, FSF, and GACF; 2D for RSF and OCR) with inverse-square calculation (ISF-OCR). The outputs of 273 combinations of R and M covering total 24 options were measured to test the model. To minimize fluence perturbation, scattered dose from range compensator and patient was not considered. The percent differences between the predicted (P) and measured (M) outputs were calculated to test the prediction accuracy ([P-M]/Mx100%). Results: GACF was required because of up to 3.5% output variation dependence on the gantry angle. A 2D interpolation was required for OCR because the dose distribution was not radially symmetric especially for the deep options. The average percent differences were −0.03±0.98% (mean±SD) and the differences of all the measurements fell within ±3%. Conclusion: It is concluded that the model can be clinically used for the compact passively scattered proton therapy system. However, great care should be taken when the field-size is less than 5×5 cm{sup 2} where a direct output measurement is required due to substantial output change by irregular block shape.« less

Silicon microneedle array for minimally invasive human health monitoring

NASA Astrophysics Data System (ADS)

Smith, Rosemary L.; Collins, Scott D.; Duy, Janice; Minogue, Timothy D.

2018-02-01

A silicon microneedle array with integrated microfluidic channels is presented, which is designed to extract dermal interstitial fluid (ISF) for biochemical analysis. ISF is a cell-free biofluid that is known to contain many of the same constituents as blood plasma, but the scope and dynamics of biomarker similarities are known for only a few components, most notably glucose. Dermal ISF is accessible just below the outer skin layer (epidermis), which can be reached and extracted with minimal sensation and tissue trauma by using a microneedle array. The microneedle arrays presented here are being developed to extract dermal ISF for off-chip profiling of nucleic acid constituents in order to identify potential biomarkers of disease. In order to assess sample volume requirements, preliminary RNA profiling was performed with suction blister ISF. The microneedles are batch fabricated using established silicon technology (low cost), are small in size, and can be integrated with sensors for on-chip analysis. This approach portends a more rapid, less expensive, self-administered assessment of human health than is currently achievable with blood sampling, especially in non-clinical and austere settings. Ultimately, a wearable device for monitoring a person's health in any setting is envisioned.

Lymphatic drainage system of the brain: A novel target for intervention of neurological diseases.

PubMed

Sun, Bao-Liang; Wang, Li-Hua; Yang, Tuo; Sun, Jing-Yi; Mao, Lei-Lei; Yang, Ming-Feng; Yuan, Hui; Colvin, Robert A; Yang, Xiao-Yi

2017-09-10

The belief that the vertebrate brain functions normally without classical lymphatic drainage vessels has been held for many decades. On the contrary, new findings show that functional lymphatic drainage does exist in the brain. The brain lymphatic drainage system is composed of basement membrane-based perivascular pathway, a brain-wide glymphatic pathway, and cerebrospinal fluid (CSF) drainage routes including sinus-associated meningeal lymphatic vessels and olfactory/cervical lymphatic routes. The brain lymphatic systems function physiological as a route of drainage for interstitial fluid (ISF) from brain parenchyma to nearby lymph nodes. Brain lymphatic drainage helps maintain water and ion balance of the ISF, waste clearance, and reabsorption of macromolecular solutes. A second physiological function includes communication with the immune system modulating immune surveillance and responses of the brain. These physiological functions are influenced by aging, genetic phenotypes, sleep-wake cycle, and body posture. The impairment and dysfunction of the brain lymphatic system has crucial roles in age-related changes of brain function and the pathogenesis of neurovascular, neurodegenerative, and neuroinflammatory diseases, as well as brain injury and tumors. In this review, we summarize the key component elements (regions, cells, and water transporters) of the brain lymphatic system and their regulators as potential therapeutic targets in the treatment of neurologic diseases and their resulting complications. Finally, we highlight the clinical importance of ependymal route-based targeted gene therapy and intranasal drug administration in the brain by taking advantage of the unique role played by brain lymphatic pathways in the regulation of CSF flow and ISF/CSF exchange. Copyright © 2017. Published by Elsevier Ltd.

Understanding the functions and relationships of the glymphatic system and meningeal lymphatics.

PubMed

Louveau, Antoine; Plog, Benjamin A; Antila, Salli; Alitalo, Kari; Nedergaard, Maiken; Kipnis, Jonathan

2017-09-01

Recent discoveries of the glymphatic system and of meningeal lymphatic vessels have generated a lot of excitement, along with some degree of skepticism. Here, we summarize the state of the field and point out the gaps of knowledge that should be filled through further research. We discuss the glymphatic system as a system that allows CNS perfusion by the cerebrospinal fluid (CSF) and interstitial fluid (ISF). We also describe the recently characterized meningeal lymphatic vessels and their role in drainage of the brain ISF, CSF, CNS-derived molecules, and immune cells from the CNS and meninges to the peripheral (CNS-draining) lymph nodes. We speculate on the relationship between the two systems and their malfunction that may underlie some neurological diseases. Although much remains to be investigated, these new discoveries have changed our understanding of mechanisms underlying CNS immune privilege and CNS drainage. Future studies should explore the communications between the glymphatic system and meningeal lymphatics in CNS disorders and develop new therapeutic modalities targeting these systems.

Effects of growth hormone-releasing hormone on sleep and brain interstitial fluid amyloid-β in an APP transgenic mouse model.

PubMed

Liao, Fan; Zhang, Tony J; Mahan, Thomas E; Jiang, Hong; Holtzman, David M

2015-07-01

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by impairment of cognitive function, extracellular amyloid plaques, intracellular neurofibrillary tangles, and synaptic and neuronal loss. There is substantial evidence that the aggregation of amyloid β (Aβ) in the brain plays a key role in the pathogenesis of AD and that Aβ aggregation is a concentration dependent process. Recently, it was found that Aβ levels in the brain interstitial fluid (ISF) are regulated by the sleep-wake cycle in both humans and mice; ISF Aβ is higher during wakefulness and lower during sleep. Intracerebroventricular infusion of orexin increased wakefulness and ISF Aβ levels, and chronic sleep deprivation significantly increased Aβ plaque formation in amyloid precursor protein transgenic (APP) mice. Growth hormone-releasing hormone (GHRH) is a well-documented sleep regulatory substance which promotes non-rapid eye movement sleep. GHRHR(lit/lit) mice that lack functional GHRH receptor have shorter sleep duration and longer wakefulness during light periods. The current study was undertaken to determine whether manipulating sleep by interfering with GHRH signaling affects brain ISF Aβ levels in APPswe/PS1ΔE9 (PS1APP) transgenic mice that overexpress mutant forms of APP and PSEN1 that cause autosomal dominant AD. We found that intraperitoneal injection of GHRH at dark onset increased sleep and decreased ISF Aβ and that delivery of a GHRH antagonist via reverse-microdialysis suppressed sleep and increased ISF Aβ. The diurnal fluctuation of ISF Aβ in PS1APP/GHRHR(lit/lit) mice was significantly smaller than that in PS1APP/GHRHR(lit/+) mice. However despite decreased sleep in GHRHR deficient mice, this was not associated with an increase in Aβ accumulation later in life. One of several possibilities for the finding is the fact that GHRHR deficient mice have GHRH-dependent but sleep-independent factors which protect against Aβ deposition. Copyright © 2014 Elsevier Inc. All rights reserved.

Cytokine profiles in interstitial fluid from chronic atopic dermatitis skin.

PubMed

Szegedi, K; Lutter, R; Res, P C; Bos, J D; Luiten, R M; Kezic, S; Middelkamp-Hup, M A

2015-11-01

The in vivo levels of inflammatory mediators in chronic atopic dermatitis (AD) skin are not well-defined due to the lack of a non-invasive or minimally invasive sampling technique. To investigate the cytokine milieu in interstitial fluid (ISF) collected from chronic lesional AD skin as compared to ISF from non-lesional AD skin and/or healthy donor skin. ISF was obtained using a minimally invasive technique of creating micropores in the skin by a laser, and harvesting ISF through aspiration. We determined the levels of 33 cytokines by Luminex and ELISA in ISF and plasma from sixteen AD patients and twelve healthy individuals. In seven AD patients, we analysed the IL-13, IL-31, IL-17, IL-22 and IFN-γ production by T cells isolated from lesional skin. AD patients were genotyped for the filaggrin gene (FLG)-null mutations 2282del4, R501X, R2447X and S3247X. Twenty-five of 33 examined mediators were detected in the ISF. The levels of IL-1α, IL-1β, IL-18, IL-1RA, IL-5, IL-13, IL-6, IL-8, TNF-α, RANTES(CCL-5), MIG(CXCL-9), IP-10(CXCL-10), TARC(CCL-17), VEGF and G-CSF showed significant differences between either lesional, non-lesional and/or healthy skin. IP-10 levels in ISF from lesional and non-lesional AD skin showed significant correlation with IP-10 blood levels. IP-10 also showed a significant correlation with clinical severity (SCORAD), as did IL-13. Levels of both IP-10 and IL-13 were more pronounced in patients with FLG-null mutations. Furthermore, FLG-null mutation carriers had more severe AD. The presented minimally invasive technique is a valuable tool to determine the in vivo cytokine profile of AD skin. © 2015 European Academy of Dermatology and Venereology.

An improved stochastic fractal search algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Sun, Chuan; Wang, Bin; Wang, Xiaojun

2018-05-03

Protein structure prediction (PSP) is a significant area for biological information research, disease treatment, and drug development and so on. In this paper, three-dimensional structures of proteins are predicted based on the known amino acid sequences, and the structure prediction problem is transformed into a typical NP problem by an AB off-lattice model. This work applies a novel improved Stochastic Fractal Search algorithm (ISFS) to solve the problem. The Stochastic Fractal Search algorithm (SFS) is an effective evolutionary algorithm that performs well in exploring the search space but falls into local minimums sometimes. In order to avoid the weakness, Lvy flight and internal feedback information are introduced in ISFS. In the experimental process, simulations are conducted by ISFS algorithm on Fibonacci sequences and real peptide sequences. Experimental results prove that the ISFS performs more efficiently and robust in terms of finding the global minimum and avoiding getting stuck in local minimums.

Effects of soybean isoflavone on intestinal antioxidant capacity and cytokines in young piglets fed oxidized fish oil.

PubMed

Huang, Lin; Ma, Xian-Yong; Jiang, Zong-Yong; Hu, You-Jun; Zheng, Chun-Tian; Yang, Xue-Fen; Wang, Li; Gao, Kai-Guo

To investigate the effect of glycitein, a synthetic soybean isoflavone (ISF), on the intestinal antioxidant capacity, morphology, and cytokine content in young piglets fed oxidized fish oil, 72 4-d-old male piglets were assigned to three treatments. The control group was fed a basal diet containing fresh fish oil, and the other two groups received the same diet except for the substitution with the same dosage of oxidized fish oil alone or with ISF (oxidized fish oil plus ISF). After 21 d of feeding, supplementation of oxidized fish oil increased the levels of malondialdehyde (MDA), oxidized glutathione (GSSG), interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), interleukin-2 (IL-2), nuclear factor κ B (NF-κB), inducible nitric oxide synthase (iNOS), NO, and Caspase-3 in jejunal mucosa, and decreased the villous height in duodenum and the levels of secretory immunoglobulin A (sIgA) and IL-4 in the jejunal mucosa compared with supplementation with fresh oil. The addition of oxidized fish oil plus ISF partially alleviated this negative effect. The addition of oxidized fish oil plus ISF increased the villous height and levels of sIgA and IL-4 in jejunal mucosa, but decreased the levels of IL-1β and IL-2 in jejunal mucosa (P<0.05) compared with oxidized fish oil. Collectively, these results show that dietary supplementation of ISF could partly alleviate the negative effect of oxidized fish oil by improving the intestinal morphology as well as the antioxidant capacity and immune function in young piglets.

Testing the implementation and sustainment facilitation (ISF) strategy as an effective adjunct to the Addiction Technology Transfer Center (ATTC) strategy: study protocol for a cluster randomized trial.

PubMed

Garner, Bryan R; Zehner, Mark; Roosa, Mathew R; Martino, Steve; Gotham, Heather J; Ball, Elizabeth L; Stilen, Patricia; Speck, Kathryn; Vandersloot, Denna; Rieckmann, Traci R; Chaple, Michael; Martin, Erika G; Kaiser, David; Ford, James H

2017-11-17

Improving the extent to which evidence-based practices (EBPs)-treatments that have been empirically shown to be efficacious or effective-are integrated within routine practice is a well-documented challenge across numerous areas of health. In 2014, the National Institute on Drug Abuse funded a type 2 effectiveness-implementation hybrid trial titled the substance abuse treatment to HIV Care (SAT2HIV) Project. Aim 1 of the SAT2HIV Project tests the effectiveness of a motivational interviewing-based brief intervention (MIBI) for substance use as an adjunct to usual care within AIDS service organizations (ASOs) as part of its MIBI Experiment. Aim 2 of the SAT2HIV Project tests the effectiveness of implementation and sustainment facilitation (ISF) as an adjunct to the Addiction Technology Transfer Center (ATTC) model for training staff in motivational interviewing as part of its ISF Experiment. The current paper describes the study protocol for the ISF Experiment. Using a cluster randomized design, case management and leadership staff from 39 ASOs across the United States were randomized to receive either the ATTC strategy (control condition) or the ATTC + ISF strategy (experimental condition). The ATTC strategy is staff-focused and includes 10 discrete strategies (e.g., provide centralized technical assistance, conduct educational meetings, provide ongoing consultation). The ISF strategy is organization-focused and includes seven discrete strategies (e.g., use an implementation advisor, organize implementation team meetings, conduct cyclical small tests of change). Building upon the exploration-preparation-implementation-sustainment (EPIS) framework, the effectiveness of the ISF strategy is examined via three staff-level measures: (1) time-to-proficiency (i.e., preparation phase outcome), (2) implementation effectiveness (i.e., implementation phase outcome), and (3) level of sustainment (i.e., sustainment phase outcome). Although not without limitations, the ISF experiment has several strengths: a highly rigorous design (randomized, hypothesis-driven), high-need setting (ASOs), large sample size (39 ASOs), large geographic representation (23 states and the District of Columbia), and testing along multiple phases of the EPIS continuum (preparation, implementation, and sustainment). Thus, study findings will significantly improve generalizable knowledge regarding the best preparation, implementation, and sustainment strategies for advancing EBPs along the EPIS continuum. Moreover, increasing ASO's capacity to address substance use may improve the HIV Care Continuum. Trial registration ClinicalTrials.gov: NCT03120598.

Absolute quantitation of isoforms of post-translationally modified proteins in transgenic organism.

PubMed

Li, Yaojun; Shu, Yiwei; Peng, Changchao; Zhu, Lin; Guo, Guangyu; Li, Ning

2012-08-01

Post-translational modification isoforms of a protein are known to play versatile biological functions in diverse cellular processes. To measure the molar amount of each post-translational modification isoform (P(isf)) of a target protein present in the total protein extract using mass spectrometry, a quantitative proteomic protocol, absolute quantitation of isoforms of post-translationally modified proteins (AQUIP), was developed. A recombinant ERF110 gene overexpression transgenic Arabidopsis plant was used as the model organism for demonstration of the proof of concept. Both Ser-62-independent (14)N-coded synthetic peptide standards and (15)N-coded ERF110 protein standard isolated from the heavy nitrogen-labeled transgenic plants were employed simultaneously to determine the concentration of all isoforms (T(isf)) of ERF110 in the whole plant cell lysate, whereas a pair of Ser-62-dependent synthetic peptide standards were used to quantitate the Ser-62 phosphosite occupancy (R(aqu)). The P(isf) was finally determined by integrating the two empirically measured variables using the following equation: P(isf) = T(isf) · R(aqu). The absolute amount of Ser-62-phosphorylated isoform of ERF110 determined using AQUIP was substantiated with a stable isotope labeling in Arabidopsis-based relative and accurate quantitative proteomic approach. The biological role of the Ser-62-phosphorylated isoform was demonstrated in transgenic plants.

Measurement of glucose area under the curve using minimally invasive interstitial fluid extraction technology: evaluation of glucose monitoring concepts without blood sampling.

PubMed

Sato, Toshiyuki; Okada, Seiki; Hagino, Kei; Asakura, Yoshihiro; Kikkawa, Yasuo; Kojima, Junko; Watanabe, Toshihiro; Maekawa, Yasunori; Isobe, Kazuki; Koike, Reona; Nakajima, Hiromu; Asano, Kaoru

2011-12-01

Monitoring postprandial hyperglycemia is crucial in treating diabetes, although its dynamics make accurate monitoring difficult. We developed a new technology for monitoring postprandial hyperglycemia using interstitial fluid (ISF) extraction technology without blood sampling. The glucose area under the curve (AUC) using this system was measured as accumulated ISF glucose (IG) with simultaneous calibration with sodium ions. The objective of this study was to evaluate this technological concept in healthy individuals. Minimally invasive ISF extraction technology (MIET) comprises two steps: pretreatment with microneedles and ISF accumulation over a specific time by contact with a solvent. The correlation between glucose and sodium ion levels using MIET was evaluated in 12 subjects with stable blood glucose (BG) levels during fasting. BG and IG time courses were evaluated in three subjects to confirm their relationship while BG was fluctuating. Furthermore, the accuracy of glucose AUC measurements by MIET was evaluated several hours after a meal in 30 subjects. A high correlation was observed between glucose and sodium ion levels when BG levels were stable (R=0.87), indicating that sodium ion is a good internal standard for calibration. The variation in IG and BG with MIET was similar, indicating that IG is an adequate substitute for BG. Finally, we showed a strong correlation (R=0.92) between IG-AUC and BG-AUC after a meal. These findings validate the adequacy of glucose AUC measurements using MIET. Monitoring glucose using MIET without blood sampling may be beneficial to patients with diabetes.

Impairment of paravascular clearance pathways in the aging brain.

PubMed

Kress, Benjamin T; Iliff, Jeffrey J; Xia, Maosheng; Wang, Minghuan; Wei, Helen S; Zeppenfeld, Douglas; Xie, Lulu; Kang, Hongyi; Xu, Qiwu; Liew, Jason A; Plog, Benjamin A; Ding, Fengfei; Deane, Rashid; Nedergaard, Maiken

2014-12-01

In the brain, protein waste removal is partly performed by paravascular pathways that facilitate convective exchange of water and soluble contents between cerebrospinal fluid (CSF) and interstitial fluid (ISF). Several lines of evidence suggest that bulk flow drainage via the glymphatic system is driven by cerebrovascular pulsation, and is dependent on astroglial water channels that line paravascular CSF pathways. The objective of this study was to evaluate whether the efficiency of CSF-ISF exchange and interstitial solute clearance is impaired in the aging brain. CSF-ISF exchange was evaluated by in vivo and ex vivo fluorescence microscopy and interstitial solute clearance was evaluated by radiotracer clearance assays in young (2-3 months), middle-aged (10-12 months), and old (18-20 months) wild-type mice. The relationship between age-related changes in the expression of the astrocytic water channel aquaporin-4 (AQP4) and changes in glymphatic pathway function was evaluated by immunofluorescence. Advancing age was associated with a dramatic decline in the efficiency of exchange between the subarachnoid CSF and the brain parenchyma. Relative to the young, clearance of intraparenchymally injected amyloid-β was impaired by 40% in the old mice. A 27% reduction in the vessel wall pulsatility of intracortical arterioles and widespread loss of perivascular AQP4 polarization along the penetrating arteries accompanied the decline in CSF-ISF exchange. We propose that impaired glymphatic clearance contributes to cognitive decline among the elderly and may represent a novel therapeutic target for the treatment of neurodegenerative diseases associated with accumulation of misfolded protein aggregates. © 2014 American Neurological Association.

Influence of part orientation on the geometric accuracy in robot-based incremental sheet metal forming

NASA Astrophysics Data System (ADS)

Störkle, Denis Daniel; Seim, Patrick; Thyssen, Lars; Kuhlenkötter, Bernd

2016-10-01

This article describes new developments in an incremental, robot-based sheet metal forming process (`Roboforming') for the production of sheet metal components for small lot sizes and prototypes. The dieless kinematic-based generation of the shape is implemented by means of two industrial robots, which are interconnected to a cooperating robot system. Compared to other incremental sheet metal forming (ISF) machines, this system offers high geometrical form flexibility without the need of any part-dependent tools. The industrial application of ISF is still limited by certain constraints, e.g. the low geometrical accuracy. Responding to these constraints, the authors present the influence of the part orientation and the forming sequence on the geometric accuracy. Their influence is illustrated with the help of various experimental results shown and interpreted within this article.

Enhancing teen pregnancy prevention in local communities: capacity building using the interactive systems framework.

PubMed

Duffy, Jennifer L; Prince, Mary Severson; Johnson, Erin E; Alton, Forrest L; Flynn, Shannon; Faye, Amy Mattison; Padgett, Polly Edwards; Rollison, Chris; Becker, Dana; Hinzey, Angela L

2012-12-01

Getting To Outcomes (GTO), an innovative framework for planning, implementing, evaluating, and sustaining interventions has been shown to be effective in helping community-based organizations (CBOs) introduce science-based approaches into their prevention work. However, the Interactive Systems Framework (ISF) suggests that adopting innovations like GTO requires a significant amount of capacity building through training and technical assistance (T/TA). In this study, 11 CBOs and three schools in South Carolina entered into a 3 year program of intense and proactive T/TA based on the ISF to learn how to apply an adaptation of GTO (Promoting Science-Based Approaches-Getting To Outcomes, PSBA-GTO) to their teen pregnancy prevention programs. Using semi-structured interviews, the partnering organizations were assessed at three points in time, pre-T/TA, 12 months, and post T/TA (30 months) for their performance of the steps of GTO in their work. The seven organizations which participated in T/TA until the end of the project received an average of 76 h of TA and 112 h of training per organization. Interview results showed increased performance of all 10 steps of PSBA-GTO by these organizations when conducting their teen pregnancy programs. These results suggest targeted and proactive T/TA can successfully bridge the gap between research and practice by using a three part delivery system, as prescribed in the ISF, which relies on an intermediary prevention support system to ensure accurate and effective translation of research to the everyday work of community-based practitioners.

Effect of interstitial and substitution alloying elements on the intrinsic stacking fault energy of nanocrystalline fcc-iron by atomistic simulation study

NASA Astrophysics Data System (ADS)

Mohammadzadeh, Mina; Mohammadzadeh, Roghayeh

2017-11-01

The stacking fault energy (SFE) is an important parameter in the deformation mechanism of face centered cubic (fcc) iron-based alloy. In this study, the effect of interstitial (C and N) and substitution (Nb and Ti) alloying elements on the intrinsic SFE (ISFE) of nanocrystalline iron were investigated via molecular dynamics (MD) simulation. The modified embedded atom method (MEAM) inter-atomic potential was used in the MD simulations. The results demonstrate a strong dependence of ISFE with addition of interstitial alloying elements but only a mild increase in ISFE with addition of substitution alloying elements in the composition range of 0 < {CNb, CTi} < 3 (at%). Moreover, it is shown that alloying of fcc iron with N decreases ISFE, whereas it increases significantly by addition of carbon element [0 < {CC, CN} < 3.5 (at%)]. The simulation method employed in this work shows reasonable agreement with some published experimental/calculated data.

Isolation, characterization and genomic analysis of a novel lytic bacteriophage vB_SsoS-ISF002 infecting Shigella sonnei and Shigella flexneri.

PubMed

Shahin, Khashayar; Bouzari, Majid; Wang, Ran

2018-03-01

Shigellosis is one of the most important food-borne and water-borne diseases worldwide. Although antibiotics are considered as efficient agents for shigellosis treatment, improper use of these has led to the emergence of antibiotic-resistant Shigella spp. Therefore, finding a new strategy as alternative treatment seems necessary. Different samples from a wastewater treatment plant were used to isolate Shigella spp. specific phages. Physiological properties were determined, and genomic analysis was also carried out. A virulent Siphoviridae bacteriophage, vB_SsoS-ISF002, was isolated from urban wastewater in Iran and showed infectivity to different isolates of both Shigella sonnei and Shigella flexneri. vB_SsoS-ISF002 was stable at different pH values and temperatures. It had a short latent period (15 min), a large burst size (76±9 p.f.u. cell -1 ) and appropriate lytic activity especially at high MOI. Its genome (dsDNA) was 50 564 bp with 45.53 % GC content and 76 predicted open reading frames. According to comparative genomic analysis and phylogenic tree construction, vB_SsoS-ISF002 was considered as a member of the T1virus genus. These results indicated that vB_SsoS-ISF002 is a novel virulent T1virus phage and may have potential as an alternative treatment for shigellosis.

Drowning stars: Reassessing the role of astrocytes in brain edema

PubMed Central

Thrane, Alexander S.; Thrane, Vinita Rangroo; Nedergaard, Maiken

2014-01-01

Edema formation frequently complicates brain infarction, tumors and trauma. Despite the significant mortality of this condition, current treatment options are often ineffective or incompletely understood. Recent studies have revealed the existence of a brain-wide paravascular pathway for cerebrospinal (CSF) and interstitial fluid (ISF) exchange. The current review critically examines the contribution of this ‘glymphatic’ system to the main types of brain edema. We propose that in cytotoxic edema, energy depletion enhances glymphatic CSF influx, whilst suppressing ISF efflux. We also argue that paravascular inflammation or ‘paravasculitis’ plays a critical role in vasogenic edema. Finally, recent advances in diagnostic imaging of glymphatic function may hold the key to defining the edema profile of individual patients and thus enable more targeted therapy. PMID:25236348

Process Improvements: Aerobic Food Waste Composting at ISF Academy

NASA Astrophysics Data System (ADS)

Lau, Y. K.

2015-12-01

ISF Academy, a school with 1500 students in Hong Kong, installed an aerobic food waste composting system in November of 2013. The system has been operational for over seven months; we will be making improvements to the system to ensure the continued operational viability and quality of the compost. As a school we are committed to reducing our carbon footprint and the amount of waste we send to the local landfill. Over an academic year we produce approximately 27 metric tons of food waste. Our system processes the food waste to compost in 14 days and the compost is used by our primary school students in a organic farming project.There are two areas of improvement: a) if the composting system becomes anaerobic, there is an odor problem that is noticed by the school community; we will be testing the use of a bio-filter to eliminate the odor problem and, b) we will be working with an equipment vendor from Australia to install an improved grease trap system. The grease and oil that is collected will be sold to a local company here in Hong Kong that processes used cooking oil for making biofuels. This system will include a two stage filtration system and a heated vessel for separating the oil from the waste water.The third project will be to evaluate biodegradable cutlery for the compositing in the system. Currently, we use a significant quantity of non-biodegradable cutlery that is then thrown away after one use. Several local HK companies are selling biodegradable cutlery, but we need to evaluate the different products to determine which ones will work with our composting system. The food waste composting project at ISF Academy demonstrates the commitment of the school community to a greener environment for HK, the above listed projects will improve the operation of the system.

Two-Photon Absorption in Pentacene Dimers: The Importance of the Spacer Using Upconversion as an Indirect Route to Singlet Fission.

PubMed

Garoni, Eleonora; Zirzlmeier, Johannes; Basel, Bettina S; Hetzer, Constantin; Kamada, Kenji; Guldi, Dirk M; Tykwinski, Rik R

2017-10-11

In this proof of concept study, we show that intramolecular singlet fission (iSF) can be initiated from a singlet excited state accessed by two-photon absorption, rather than through a traditional route of direct one-photon excitation (OPE). Thus, iSF in pentacene dimers 2 and 3 is enabled through NIR irradiation at 775 nm, a wavelength where neither dimer exhibits linear absorption of light. The adamantyl and meta-phenylene spacers 2 and 3, respectively, are designed to feature superimposable geometries, which establishes that the electronic coupling between the two pentacenes is the significant structural feature that dictates iSF efficiency.

Cold climate performance analysis of on-site domestic wastewater treatment systems.

PubMed

Williamson, Eric

2010-06-01

Household on-site septic systems with secondary wastewater treatment in Anchorage, Alaska, were sampled and analyzed for performance parameters during the winter to spring months. System types included intermittent dosing sand filters (ISF), three types of recirculating trickling filters (RTF), and suspended-growth aeration tanks. Total nitrogen from the trickling filter and aeration tank effluent was fairly uniform, at approximately 30 mg/L. Total suspended solids (TSS) means were mostly less than 15 mg/L. The 5-day biochemical oxygen demand (BODs) showed considerable variability, with means ranging from 9.2 mg/ L for ISFs up to 39.5 mg/L for one type of RTF, even though this type has shown excellent results in several test programs. The data suggested that effluent temperature within the sample range had almost no effect on effluent concentrations of BOD5 or TSS and only a small effect on the removal of total nitrogen. Non-climatic factors were probably of equal importance to treatment results.

Implementation science in low-resource settings: using the interactive systems framework to improve hand hygiene in a tertiary hospital in Ghana.

PubMed

Kallam, Brianne; Pettitt-Schieber, Christie; Owen, Medge; Agyare Asante, Rebecca; Darko, Elizabeth; Ramaswamy, Rohit

2018-05-19

Low-resource clinical settings often face obstacles that challenge the implementation of recommended evidence-based practices (EBPs). Implementation science approaches are useful in identifying barriers and developing strategies to address them. Ridge Regional Hospital (RRH), a tertiary referral hospital in Accra, Ghana experienced a spike in rates of neonatal sepsis and launched a quality improvement (QI) initiative that identified poor adherence to hand hygiene in the neonatal intensive care unit as a potential source of infections. A multi-modal change package of World Health Organization-recommended solutions was created to address this issue. To ensure that the outputs of the QI effort were adopted within the organization, leaders at RRH and Kybele, Inc. used an implementation science framework called the 'Interactive Systems Framework for Dissemination and Implementation' (ISF) to create a package of locally acceptable implementation strategies. The ISF has never been used before to guide implementation in low-resource settings. Hand hygiene compliance rose from 67% to 92% overall, including a 36% increase during the night shifts-a group of healthcare workers with typically very low levels of compliance. The drastic improvement in adherence to hand hygiene suggests the potential value of the joint use of QI and implementation science to promote the creation and application of contextually appropriate EBPs in low-resource settings. Our results also suggest that using an implementation framework such as the ISF could rapidly increase the uptake of other evidence-based interventions in low-resource settings.

Drowning stars: reassessing the role of astrocytes in brain edema.

PubMed

Thrane, Alexander S; Rangroo Thrane, Vinita; Nedergaard, Maiken

2014-11-01

Edema formation frequently complicates brain infarction, tumors, and trauma. Despite the significant mortality of this condition, current treatment options are often ineffective or incompletely understood. Recent studies have revealed the existence of a brain-wide paravascular pathway for cerebrospinal (CSF) and interstitial fluid (ISF) exchange. The current review critically examines the contribution of this 'glymphatic' system to the main types of brain edema. We propose that in cytotoxic edema, energy depletion enhances glymphatic CSF influx, whilst suppressing ISF efflux. We also argue that paravascular inflammation or 'paravasculitis' plays a critical role in vasogenic edema. Finally, recent advances in diagnostic imaging of glymphatic function may hold the key to defining the edema profile of individual patients, and thus enable more targeted therapy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mercadeo Virus: A Novel Mosquito-Specific Flavivirus from Panama

PubMed Central

Carrera, Jean-Paul; Guzman, Hilda; Beltrán, Davis; Díaz, Yamilka; López-Vergès, Sandra; Torres-Cosme, Rolando; Popov, Vsevolod; Widen, Steven G.; Wood, Thomas G.; Weaver, Scott C.; Cáceres-Carrera, Lorenzo; Vasilakis, Nikos; Tesh, Robert B.

2015-01-01

Viruses in the genus Flavivirus (family Flaviviridae) include many arthropod-borne viruses of public health and veterinary importance. However, during the past two decades an explosion of novel insect-specific flaviviruses (ISFs), some closely related to vertebrate pathogens, have been discovered. Although many flavivirus pathogens of vertebrates have been isolated from naturally infected mosquitoes in Panama, ISFs have not previously been reported from the country. This report describes the isolation and characterization of a novel ISF, tentatively named Mercadeo virus (MECDV), obtained from Culex spp. mosquitoes collected in Panama. Two MECDV isolates were sequenced and cluster phylogenetically with cell-fusing agent virus (CFAV) and Nakiwogo virus (NAKV) to form a distinct lineage within the insect-specific group of flaviviruses. PMID:26304915

Long-Lived Triplet Excited States of Bent-Shaped Pentacene Dimers by Intramolecular Singlet Fission.

PubMed

Sakuma, Takao; Sakai, Hayato; Araki, Yasuyuki; Mori, Tadashi; Wada, Takehiko; Tkachenko, Nikolai V; Hasobe, Taku

2016-03-24

Intramolecular singlet fission (ISF) is a promising photophysical process to construct more efficient light energy conversion systems as one excited singlet state converts into two excited triplet states. Herein we synthesized and evaluated bent-shaped pentacene dimers as a prototype of ISF to reveal intrinsic characters of triplet states (e.g., lifetimes of triplet excited states). In this study, meta-phenylene-bridged TIPS-pentacene dimer (PcD-3Ph) and 2,2'-bipheynyl bridged TIPS-pentacene dimer (PcD-Biph) were newly synthesized as bent-shaped dimers. In the steady-state spectroscopy, absorption and emission bands of these dimers were fully characterized, suggesting the appropriate degree of electronic coupling between pentacene moieties in these dimers. In addition, the electrochemical measurements were also performed to check the electronic interaction between two pentacene moieties. Whereas the successive two oxidation peaks owing to the delocalization were observed in a directly linked-pentacene dimer (PcD) by a single bond, the cyclic voltammograms in PcD-Biph and PcD-3Ph implied the weaker interaction compared to that of p-phenylene-bridged TIPS-pentacene dimer (PcD-4Ph) and PcD. The femtosecond and nanosecond transient absorption spectra clearly revealed the slower ISF process in bent-shaped pentacene dimers (PcD-Biph and PcD-3Ph), more notably, the slower relaxation of the excited triplet states in PcD-Biph and PcD-3Ph. Namely, the quantum yields of triplet states (ΦT) by ISF approximately remain constant (ca. 180-200%) in all dimer systems, whereas the lifetimes of the triplet excited states became much longer (up to 360 ns) in PcD-Biph as compared to PcD-4Ph (15 ns). Additionally, the lifetimes of the corresponding triplet states in PcD-Biph and PcD-3Ph were sufficiently affected by solvent viscosity. In particular, the lifetimes of PcD-Biph triplet state in THF/paraffin (1.0 μs) increased up to approximately three times as compared to that in THF (360 ns), whereas those of PcD-4Ph were quite similar in both solvent.

Interstitial fluid drainage is impaired in ischemic stroke and Alzheimer’s disease mouse models

PubMed Central

Arbel-Ornath, Michal; Hudry, Eloise; Eikermann-Haerter, Katharina; Hou, Steven; Gregory, Julia L.; Zhao, Lingzhi; Betensky, Rebecca A.; Frosch, Matthew P.; Greenberg, Steven M.; Bacskai, Brian J.

2013-01-01

The interstitial fluid (ISF) drainage pathway has been hypothesized to underlie the clearance of solutes and metabolites from the brain. Previous work has implicated the perivascular spaces along arteries as the likely route for ISF clearance, however it has never been demonstrated directly. The accumulation of amyloid β (Aβ) peptides in brain parenchyma is one of the pathological hallmarks of Alzheimer disease (AD), and it is likely related to an imbalance between production and clearance of the peptide. Aβ drainage along perivascular spaces has been postulated to be one of the mechanisms that mediates the peptide clearance from the brain. We therefore devised a novel method to visualize solute clearance in real time in the living mouse brain using laser guided bolus dye injections and multiphoton imaging. This methodology allows high spatial and temporal resolution and revealed the kinetics of ISF clearance. We found that the ISF drains along perivascular spaces of arteries and capillaries but not veins, and its clearance exhibits a bi-exponential profile. ISF drainage requires a functional vasculature, as solute clearance decreased when perfusion was impaired. In addition, reduced solute clearance was observed in transgenic mice with significant vascular amyloid deposition; we suggest the existence of a feed-forward mechanism, by which amyloid deposition promotes further amyloid deposition. This important finding provides a mechanistic link between cerebrovascular disease and Alzheimer disease and suggests that facilitation of Aβ clearance along the perivascular pathway should be considered as a new target for therapeutic approaches to AD and CAA. PMID:23818064

Integrated skin flash planning technique for intensity-modulated radiation therapy for vulvar cancer prevents marginal misses and improves superficial dose coverage.

PubMed

Dyer, Brandon A; Jenshus, Abriel; Mayadev, Jyoti S

2018-02-28

Radiation therapy (RT) plays a definitive role in locally advanced vulvar cancer, and in the adjuvant setting with high risk postoperative features after wide local excision. There is significant morbidity associated with traditional, large RT fields using 2D or 3D techniques, and the use of intensity-modulated radiation therapy (IMRT) in vulvar cancer is increasing. However, there remains a paucity of technical information regarding the prevention of a marginal miss during the treatment planning process. The use of an integrated skin flash (ISF) during RT planning can be used to account for anatomic variation, and intra- and interfraction motion seen during treatment. Herein we present the case of a patient with a T1aN0M0, Stage IA vulva cancer to illustrate the progressive vulvar swelling and lymph edema seen during treatment and retrospectively evaluate the dosimetric effects of using an ISF RT plan vs standard RT planning techniques. Standard planning techniques to treat vulvar cancer patients with IMRT do not sufficiently account for the change in patient anatomy and can lead to a marginal miss. ISF is an RT planning technique that can decrease the risk of a marginal miss and the technique is easily implemented during the planning stages of RT treatment. Furthermore, use of an ISF technique can improve vulvar clinical target volume coverage and plan homogeneity. Based on our experience, and this study, a 2-cm ISF is suggested to account for variations in daily clinical setup and changes in patient anatomy during treatment. Published by Elsevier Inc.

Plasticity mechanisms in HfN at elevated and room temperature.

PubMed

Vinson, Katherine; Yu, Xiao-Xiang; De Leon, Nicholas; Weinberger, Christopher R; Thompson, Gregory B

2016-10-06

HfN specimens deformed via four-point bend tests at room temperature and at 2300 °C (~0.7 T m ) showed increased plasticity response with temperature. Dynamic diffraction via transmission electron microscopy (TEM) revealed ⟨110⟩{111} as the primary slip system in both temperature regimes and ⟨110⟩{110} to be a secondary slip system activated at elevated temperature. Dislocation line lengths changed from a primarily linear to a curved morphology with increasing temperature suggestive of increased dislocation mobility being responsible for the brittle to ductile temperature transition. First principle generalized stacking fault energy calculations revealed an intrinsic stacking fault (ISF) along ⟨112⟩{111}, which is the partial dislocation direction for slip on these close packed planes. Though B1 structures, such as NaCl and HfC predominately slip on ⟨110⟩{110}, the ISF here is believed to facilitate slip on the {111} planes for this B1 HfN phase.

Photochemical Dynamics of Intramolecular Singlet Fission

NASA Astrophysics Data System (ADS)

Lin, Zhou; Iwasaki, Hikari; Van Voorhis, Troy

2017-06-01

Singlet fission (SF) converts a singlet exciton (S_1) into a pair of triplet ones (T_1) via a ``multi-exciton'' (ME) intermediate: S_1 \\longleftrightarrow ^1ME \\longleftrightarrow ^1(T_1T_1) \\longrightarrow 2T_1. In exothermic cases, e.g., crystalline pentacene or its derivatives, the quantum yield of SF can reach 200%. With SF doubling the electric current generated by an incident high-energy photon, the solar conversion efficiency in pentacene-based organic photovoltaics (OPVs) can exceed the Shockley-Queisser limit of 33.7%. The ME state is popularly considered to be a dimeric state with significant charge transfer (CT) character that is strongly coupled to both S_1 and ^1(T_1T_1), while this local model lacks strong support from full quantum dynamics studies. Intramolecular SF (ISF) occurring to covalently-bound dimers in the solution phase is an excellent model for a straightforward dynamics simulation of local excitons. In the present study, we investigate the ISF mechanisms for three covalently-bound dimers of pentacene derivatives, including ortho-, meta-, and para-bis(6,13-bis(triisopropylsilylethynyl)pentacene)benzene, in non-protic solvents. Specifically, we propagate the real-time, non-adiabatic quantum mechanical/molecular mechanical (QM/MM) dynamics on the potential energy surfaces associated with the states of S_1, ^1(T_1T_1) and CT. We explore how the energies of these ISF-relevant states and the non-adiabatic couplings between each other fluctuate with time and the instantaneous molecular configuration (e.g., intermonomer distance and orientation). We also quantitatively compare Condon and non-Condon ISF dynamics with solution-phase spectroscopic data. Our results allow us to understand the roles of CT energy levels in the ISF mechanism and propose a design strategy to maximize ISF efficiency. M. B. Smith and J. Michl, Chem. Rev. 110, 6891 (2010). W. Shockley and H. J. Queisser, J. Appl. Phys. 32, 510 (1961). T. C. Berkelbach, M. S. Hybertsen, and D. R. Reichman, J. Chem. Phys. 141, 074705 (2014). M. G. Mavros, D. Hait, and T. A. Van Voorhis, J. Chem. Phys. 145, 214105 (2016). V. Vaissier, and T. A. Van Voorhis, in preparation.

Periodic Extraction of Interstitial Fluid from the Site of Subcutaneous Insulin Infusion for the Measurement of Glucose: A Novel Single-Port Technique for the Treatment of Type 1 Diabetes Patients

PubMed Central

Lindpointner, Stefan; Korsatko, Stefan; Tutkur, Dina; Bodenlenz, Manfred; Pieber, Thomas R.

2013-01-01

Abstract Background Treatment of type 1 diabetes patients could be simplified if the site of subcutaneous insulin infusion could also be used for the measurement of glucose. This study aimed to assess the agreement between blood glucose concentrations and glucose levels in the interstitial fluid (ISF) that is extracted from the insulin infusion site during periodic short-term interruptions of continuous subcutaneous insulin infusion (CSII). Subjects and Methods A perforated cannula (24 gauge) was inserted into subcutaneous adipose tissue of C-peptide-negative type 1 diabetes subjects (n=13) and used alternately to infuse rapid-acting insulin (100 U/mL) and to extract ISF glucose during a fasting period and after ingestion of a standard oral glucose load (75 g). Results Although periodically interrupted for extracting glucose (every hour for approximately 10 min), insulin infusion with the cannula was adequate to achieve euglycemia during fasting and to restore euglycemia after glucose ingestion. Furthermore, the ISF-derived estimates of plasma glucose levels agreed well with plasma glucose concentrations. Correlation coefficient and median absolute relative difference values were found to be 0.95 and 8.0%, respectively. Error grid analysis showed 99.0% of all ISF glucose values within clinically acceptable Zones A and B (83.5% Zone A, 15.5% Zone B). Conclusions Results show that ISF glucose concentrations measured at the insulin infusion site during periodic short-term interruptions of CSII closely reflect blood glucose levels, thus suggesting that glucose monitoring and insulin delivery may be performed alternately at the same tissue site. A single-port device of this type could be used to simplify and improve glucose management in diabetes. PMID:23126579

A modular tooling set-up for incremental sheet forming (ISF) with subsequent stress-relief annealing under partial constraints

NASA Astrophysics Data System (ADS)

Maqbool, Fawad; Bambach, Markus

2017-10-01

Incremental sheet forming (ISF) is a manufacturing process most suitable for small-batch production of sheet metal parts. In ISF, a CNC-controlled tool moves over the sheet metal, following a specified contour to form a part of the desired geometry. This study focuses on one of the dominant process limitations associated with the ISF, i.e., the limited geometrical accuracy. In this regard, a case study is performed which shows that increased geometrical accuracy of the formed part can be achieved by a using stress-relief annealing before unclamping. To keep the tooling costs low, a modular die design consisting of a stiff metal frame and inserts made from inexpensive plastics (Sika®) were devised. After forming, the plastics inserts are removed. The metal frame supports the part during stress-relief annealing. Finite Element (FE) simulations of the manufacturing process are performed. Due to the residual stresses induced during the forming, the geometry of the formed part, from FE simulation and the actual manufacturing process, shows severe distortion upon unclamping the part. Stress relief annealing of the formed part under partial constraints exerted by the tool frame shows that a part with high geometrical accuracy can be obtained.

A dural lymphatic vascular system that drains brain interstitial fluid and macromolecules

PubMed Central

Aspelund, Aleksanteri; Antila, Salli; Proulx, Steven T.; Karlsen, Tine Veronica; Karaman, Sinem; Detmar, Michael; Wiig, Helge

2015-01-01

The central nervous system (CNS) is considered an organ devoid of lymphatic vasculature. Yet, part of the cerebrospinal fluid (CSF) drains into the cervical lymph nodes (LNs). The mechanism of CSF entry into the LNs has been unclear. Here we report the surprising finding of a lymphatic vessel network in the dura mater of the mouse brain. We show that dural lymphatic vessels absorb CSF from the adjacent subarachnoid space and brain interstitial fluid (ISF) via the glymphatic system. Dural lymphatic vessels transport fluid into deep cervical LNs (dcLNs) via foramina at the base of the skull. In a transgenic mouse model expressing a VEGF-C/D trap and displaying complete aplasia of the dural lymphatic vessels, macromolecule clearance from the brain was attenuated and transport from the subarachnoid space into dcLNs was abrogated. Surprisingly, brain ISF pressure and water content were unaffected. Overall, these findings indicate that the mechanism of CSF flow into the dcLNs is directly via an adjacent dural lymphatic network, which may be important for the clearance of macromolecules from the brain. Importantly, these results call for a reexamination of the role of the lymphatic system in CNS physiology and disease. PMID:26077718

A dural lymphatic vascular system that drains brain interstitial fluid and macromolecules.

PubMed

Aspelund, Aleksanteri; Antila, Salli; Proulx, Steven T; Karlsen, Tine Veronica; Karaman, Sinem; Detmar, Michael; Wiig, Helge; Alitalo, Kari

2015-06-29

The central nervous system (CNS) is considered an organ devoid of lymphatic vasculature. Yet, part of the cerebrospinal fluid (CSF) drains into the cervical lymph nodes (LNs). The mechanism of CSF entry into the LNs has been unclear. Here we report the surprising finding of a lymphatic vessel network in the dura mater of the mouse brain. We show that dural lymphatic vessels absorb CSF from the adjacent subarachnoid space and brain interstitial fluid (ISF) via the glymphatic system. Dural lymphatic vessels transport fluid into deep cervical LNs (dcLNs) via foramina at the base of the skull. In a transgenic mouse model expressing a VEGF-C/D trap and displaying complete aplasia of the dural lymphatic vessels, macromolecule clearance from the brain was attenuated and transport from the subarachnoid space into dcLNs was abrogated. Surprisingly, brain ISF pressure and water content were unaffected. Overall, these findings indicate that the mechanism of CSF flow into the dcLNs is directly via an adjacent dural lymphatic network, which may be important for the clearance of macromolecules from the brain. Importantly, these results call for a reexamination of the role of the lymphatic system in CNS physiology and disease. © 2015 Aspelund et al.

In-Flight Spectral Calibration of the APEX Imaging Spectrometer Using Fraunhofer Lines

NASA Astrophysics Data System (ADS)

Kuhlmann, Gerrit; Hueni, Andreas; Damm, Aalexander; Brunner, Dominik

2015-11-01

The Airborne Prism EXperiment (APEX) is an imaging spectrometer which allows to observe atmospheric trace gases such as nitrogen dioxide (NO2). Using a high resolution spectrum of solar Fraunhofer lines, APEX measurements collected during flight have been spectrally calibrated for centre wavelength positions (CW) and instrument slit function (ISF) and compared to the laboratory calibration. We find that CWs depend strongly on both across- and along-track position due to spectral smile and CWs dependency on ambient pressure. The width of the ISF is larger than estimated from the laboratory calibration but can be described by a linear scaling of the laboratory values. The ISF width depends on across- but not on along-track direction. The results demonstrate the importance of characterizing and monitoring the instrument performance during flight and will be used to improve the Empa APEX NO2 retrieval algorithm.

Novel insect-specific flavivirus isolated from northern Europe

PubMed Central

Huhtamo, Eili; Moureau, Gregory; Cook, Shelley; Julkunen, Ora; Putkuri, Niina; Kurkela, Satu; Uzcátegui, Nathalie Y.; Harbach, Ralph E.; Gould, Ernest A.; Vapalahti, Olli; de Lamballerie, Xavier

2012-01-01

Mosquitoes collected in Finland were screened for flaviviral RNA leading to the discovery and isolation of a novel flavivirus designated Hanko virus (HANKV). Virus characterization, including phylogenetic analysis of the complete coding sequence, confirmed HANKV as a member of the “insect-specific” flavivirus (ISF) group. HANKV is the first member of this group isolated from northern Europe, and therefore the first northern European ISF for which the complete coding sequence has been determined. HANKV was not transcribed as DNA in mosquito cell culture, which appears atypical for an ISF. HANKV shared highest sequence homology with the partial NS5 sequence available for the recently discovered Spanish Ochlerotatus flavivirus (SOcFV). Retrospective analysis of mitochondrial sequences from the virus-positive mosquito pool suggested an Ochlerotatus mosquito species as the most likely host for HANKV. HANKV and SOcFV may therefore represent a novel group of Ochlerotatus-hosted insect-specific flaviviruses in Europe and further afield. PMID:22999256

Cerebrospinal and Interstitial Fluid Transport via the Glymphatic Pathway Modeled by Optimal Mass Transport

PubMed Central

Ratner, Vadim; Gao, Yi; Lee, Hedok; Elkin, Rena; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2017-01-01

The glymphatic pathway is a system which facilitates continuous cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange and plays a key role in removing waste products from the rodent brain. Dysfunction of the glymphatic pathway may be implicated in the pathophysiology of Alzheimer's disease. Intriguingly, the glymphatic system is most active during deep wave sleep general anesthesia. By using paramagnetic tracers administered into CSF of rodents, we previously showed the utility of MRI in characterizing a macroscopic whole brain view of glymphatic transport but we have yet to define and visualize the specific flow patterns. Here we have applied an alternative mathematical analysis approach to a dynamic time series of MRI images acquired every 4 min over ∼3 hrs in anesthetized rats, following administration of a small molecular weight paramagnetic tracer into the CSF reservoir of the cisterna magna. We use Optimal Mass Transport (OMT) to model the glymphatic flow vector field, and then analyze the flow to find the network of CSF-ISF flow channels. We use 3D visualization computational tools to visualize the OMT defined network of CSF-ISF flow channels in relation to anatomical and vascular key landmarks from the live rodent brain. The resulting OMT model of the glymphatic transport network agrees largely with the current understanding of the glymphatic transport patterns defined by dynamic contrast-enhanced MRI revealing key CSF transport pathways along the ventral surface of the brain with a trajectory towards the pineal gland, cerebellum, hypothalamus and olfactory bulb. In addition, the OMT analysis also revealed some interesting previously unnoticed behaviors regarding CSF transport involving parenchymal streamlines moving from ventral reservoirs towards the surface of the brain, olfactory bulb and large central veins. PMID:28323163

Cerebrospinal and interstitial fluid transport via the glymphatic pathway modeled by optimal mass transport.

PubMed

Ratner, Vadim; Gao, Yi; Lee, Hedok; Elkin, Rena; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2017-05-15

The glymphatic pathway is a system which facilitates continuous cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange and plays a key role in removing waste products from the rodent brain. Dysfunction of the glymphatic pathway may be implicated in the pathophysiology of Alzheimer's disease. Intriguingly, the glymphatic system is most active during deep wave sleep general anesthesia. By using paramagnetic tracers administered into CSF of rodents, we previously showed the utility of MRI in characterizing a macroscopic whole brain view of glymphatic transport but we have yet to define and visualize the specific flow patterns. Here we have applied an alternative mathematical analysis approach to a dynamic time series of MRI images acquired every 4min over ∼3h in anesthetized rats, following administration of a small molecular weight paramagnetic tracer into the CSF reservoir of the cisterna magna. We use Optimal Mass Transport (OMT) to model the glymphatic flow vector field, and then analyze the flow to find the network of CSF-ISF flow channels. We use 3D visualization computational tools to visualize the OMT defined network of CSF-ISF flow channels in relation to anatomical and vascular key landmarks from the live rodent brain. The resulting OMT model of the glymphatic transport network agrees largely with the current understanding of the glymphatic transport patterns defined by dynamic contrast-enhanced MRI revealing key CSF transport pathways along the ventral surface of the brain with a trajectory towards the pineal gland, cerebellum, hypothalamus and olfactory bulb. In addition, the OMT analysis also revealed some interesting previously unnoticed behaviors regarding CSF transport involving parenchymal streamlines moving from ventral reservoirs towards the surface of the brain, olfactory bulb and large central veins. Copyright © 2017. Published by Elsevier Inc.

An ALMA study of the Orion Integral Filament. I. Evidence for narrow fibers in a massive cloud

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Forbrich, J.; Alves, J.; Meingast, S.; Grossschedl, J.; Teixeira, P. S.

2018-03-01

Aim. We have investigated the gas organization within the paradigmatic Integral Shape Filament (ISF) in Orion in order to decipher whether or not all filaments are bundles of fibers. Methods: We combined two new ALMA Cycle 3 mosaics with previous IRAM 30m observations to produce a high-dynamic range N2H+ (1-0) emission map of the ISF tracing its high-density material and velocity structure down to scales of 0.009 pc (or 2000 AU). Results: From the analysis of the gas kinematics, we identify a total of 55 dense fibers in the central region of the ISF. Independently of their location in the cloud, these fibers are characterized by transonic internal motions, lengths of 0.15 pc, and masses per unit length close to those expected in hydrostatic equilibrium. The ISF fibers are spatially organized forming a dense bundle with multiple hub-like associations likely shaped by the local gravitational potential. Within this complex network, the ISF fibers show a compact radial emission profile with a median FWHM of 0.035 pc systematically narrower than the previously proposed universal 0.1 pc filament width. Conclusions: Our ALMA observations reveal complex bundles of fibers in the ISF, suggesting strong similarities between the internal substructure of this massive filament and previously studied lower-mass objects. The fibers show identical dynamic properties in both low- and high-mass regions, and their widespread detection in nearby clouds suggests a preferred organizational mechanism of gas in which the physical fiber dimensions (width and length) are self-regulated depending on their intrinsic gas density. Combining these results with previous works in Musca, Taurus, and Perseus, we identify a systematic increase of the surface density of fibers as a function of the total mass per-unit-length in filamentary clouds. Based on this empirical correlation, we propose a unified star-formation scenario where the observed differences between low- and high-mass clouds, and the origin of clusters, emerge naturally from the initial concentration of fibers. The movie associated to Fig. 2 is available at http://https://www.aanda.orgThe data products of this work are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/610/A77

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Evaluation on chemical stability of lead blast furnace (LBF) and imperial smelting furnace (ISF) slags.

PubMed

Yin, Nang-Htay; Sivry, Yann; Guyot, François; Lens, Piet N L; van Hullebusch, Eric D

2016-09-15

The leaching behavior of Pb and Zn from lead blast furnace (LBF) and imperial smelting furnace (ISF) slags sampled in the North of France was studied as a function of pHs and under two atmospheres (open air and nitrogen). The leaching of major elements from the slags was monitored as a function of pH (4, 5.5, 7, 8.5 and 10) under both atmospheres for different slag-water interaction times (1 day and 9 days). The leaching results were coupled with a geochemical model; Visual MINTEQ version 3.0, and a detailed morphological and mineralogical analysis was performed on the leached slags by scanning and transmission electron microscopy (SEM and TEM). Significant amounts of Ca, Fe and Zn were released under acidic conditions (pH 4) with a decrease towards the neutral to alkaline conditions (pH 7 and 10) for both LBF and ISF slags. On the other hand, Fe leachability was limited at neutral to alkaline pH for both slags. The concentrations of all elements increased gradually after 216 h compared to initial 24 h of leaching period. The presence of oxygen under open-air atmosphere not only enhanced oxidative weathering but also encouraged formation of secondary oxide and carbonate phases. Formation of carbonates and clay minerals was suggested by Visual MINTEQ which was further confirmed by SEM & TEM. The hydration and partial dissolution of hardystonite, as well as the destabilization of amorphous glassy matrix mainly contributed to the release of major elements, whereas the spinel related oxides were resistant against pH changes and atmospheres within the time frame concerned for both LBF and ISF slags. The total amount of Pb leached out at pH 7 under both atmospheres suggested that both LBF and ISF slags are prone to weathering even at neutral environmental conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Conjoint Behavioral Consultation to Implement Evidence-Based Practices for Students in Low-Income Urban Schools

ERIC Educational Resources Information Center

Garbacz, S. Andrew; Watkins, Natasha D.; Diaz, Yamalis; Barnabas, Ernesto R., Jr.; Schwartz, Billie; Eiraldi, Ricardo

2017-01-01

The purpose of this paper is to demonstrate how Conjoint Behavioral Consultation (CBC) can be used by school behavioral health programs within the Interactive Systems Framework (ISF) as a tool for developing and supporting intervention plans that integrate mental health evidence-based practices (EBPs). External behavioral health consultants…

A Direct Mechanism of Ultrafast Intramolecular Singlet Fission in Pentacene Dimers

DOE PAGES

Fuemmeler, Eric G.; Sanders, Samuel N.; Pun, Andrew B.; ...

2016-05-05

Interest in materials that undergo singlet fission (SF) has been catalyzed by the potential to exceed the Shockley–Queisser limit of solar power conversion efficiency. In conventional materials, the mechanism of SF is an intermolecular process (xSF), which is mediated by charge transfer (CT) states and depends sensitively on crystal packing or molecular collisions. In contrast, recently reported covalently coupled pentacenes yield ~2 triplets per photon absorbed in individual molecules: the hallmark of intramolecular singlet fission (iSF). But, the mechanism of iSF is unclear. Here, using multireference electronic structure calculations and transient absorption spectroscopy, we establish that iSF can occur viamore » a direct coupling mechanism that is independent of CT states. Moreover, we show that a near-degeneracy in electronic state energies induced by vibronic coupling to intramolecular modes of the covalent dimer allows for strong mixing between the correlated triplet pair state and the local excitonic state, despite weak direct coupling.« less

Host- and microbe-related risk factors for and pathophysiology of fatal Rickettsia conorii infection in Portuguese patients.

PubMed

Sousa, Rita de; França, Ana; Dória Nòbrega, Sónia; Belo, Adelaide; Amaro, Mario; Abreu, Tiago; Poças, José; Proença, Paula; Vaz, José; Torgal, Jorge; Bacellar, Fátima; Ismail, Nahed; Walker, David H

2008-08-15

The pathophysiologic mechanisms that determine the severity of Mediterranean spotted fever (MSF) and the host-related and microbe-related risk factors for a fatal outcome are incompletely understood. This prospective study used univariate and multivariate analyses to determine the risk factors for a fatal outcome for 140 patients with Rickettsia conorii infection admitted to 13 Portuguese hospitals during 1994-2006 with documented identification of the rickettsial strain causing their infection. A total of 71 patients (51%) were infected with the Malish strain of Rickettsia conorii, and 69 (49%) were infected with the Israeli spotted fever (ISF) strain. Patients were admitted to the intensive care unit (40 [29%]), hospitalized as routine inpatients (95[67%]), or managed as outpatients (5[4%]). Death occurred in 29 adults (21%). A fatal outcome was significantly more likely for patients infected with the ISF strain, and alcoholism was a risk factor. The pathophysiology of a fatal outcome involved significantly greater incidence of petechial rash, gastrointestinal symptoms, obtundation and/or confusion, dehydration, tachypnea, hepatomegaly, leukocytosis, coagulopathy, azotemia, hyperbilirubinemia, and elevated levels of hepatic enzymes and creatine kinase. Some, but not all, of these findings were observed more often in ISF strain-infected patients. Although fatalities and similar clinical manifestations occurred among both groups of patients, the ISF strain was more virulent than the Malish strain. Multivariate analysis revealed that acute renal failure and hyperbilirubinemia were most strongly associated with a fatal outcome.

Impairment of paravascular clearance pathways in the aging brain

PubMed Central

Kress, Benjamin T.; Iliff, Jeffrey J.; Xia, Maosheng; Wang, Minghuan; Wei, Helen; Zeppenfeld, Douglas; Xie, Lulu; Kang, Hongyi; Xu, Qiwu; Liew, Jason; Plog, Benjamin A.; Ding, Fengfei; Deane, Rashid; Nedergaard, Maiken

2014-01-01

Objective In the brain, protein waste removal is partly performed by paravascular pathways that facilitate convective exchange of water and soluble contents between cerebrospinal and interstitial fluids. Several lines of evidence suggest that bulk flow drainage via the glymphatic system is driven by cerebrovascular pulsation, and is dependent on astroglial water channels that line paravascular cerebrospinal fluid (CSF) pathways. The Objective of this study was to evaluate whether the efficiency of CSF-ISF exchange and interstitial solute clearance is impaired in the aging brain. Methods CSF-ISF exchange was evaluated by in vivo and ex vivo fluorescence microscopy while interstitial solute clearance was evaluated by radio-tracer clearance assays in young (2–3 month), middle age (10–12 month) and old (18–20 month) wild type mice. The relationship between age-related changes in the expression of the astrocytic water channel aquaporin-4 (AQP4) and changes in glymphatic pathway function were evaluated by immunofluorescence. Results Advancing age was associated with a dramatic decline in the efficiency of exchange between the subarachnoid CSF and the brain parenchyma. Relative to the young, clearance of intraparechamally injected amyloid β was impaired by 40% in the old mice. A 27% reduction in the vessel wall pulsatility of intracortical arterioles and widespread loss of perivascular AQP4 polarization along the penetrating arteries accompanied the decline in CSF-ISF exchange. Interpretation We propose that impaired glymphatic clearance contributes to cognitive decline among the elderly and may represent a novel therapeutic target for the treatment of neurodegenerative diseases associated with accumulation of mis-folded protein aggregates. PMID:25204284

Direct Evidence of Acetaminophen Interference with Subcutaneous Glucose Sensing in Humans: A Pilot Study

PubMed Central

Basu, Ananda; Veettil, Sona; Dyer, Roy; Peyser, Thomas

2016-01-01

Abstract Background: Recent advances in accuracy and reliability of continuous glucose monitoring (CGM) devices have focused renewed interest on the use of such technology for therapeutic dosing of insulin without the need for independent confirmatory blood glucose meter measurements. An important issue that remains is the susceptibility of CGM devices to erroneous readings in the presence of common pharmacologic interferences. We report on a new method of assessing CGM sensor error to pharmacologic interferences using the example of oral administration of acetaminophen. Materials and Methods: We examined the responses of several different Food and Drug Administration–approved and commercially available CGM systems (Dexcom [San Diego, CA] Seven® Plus™, Medtronic Diabetes [Northridge, CA] Guardian®, and Dexcom G4® Platinum) to oral acetaminophen in 10 healthy volunteers without diabetes. Microdialysis catheters were placed in the abdominal subcutaneous tissue. Blood and microdialysate samples were collected periodically and analyzed for glucose and acetaminophen concentrations before and after oral ingestion of 1 g of acetaminophen. We compared the response of CGM sensors with the measured acetaminophen concentrations in the blood and interstitial fluid. Results: Although plasma glucose concentrations remained constant at approximately 90 mg/dL (approximately 5 mM) throughout the study, CGM glucose measurements varied between approximately 85 to 400 mg/dL (from approximately 5 to 22 mM) due to interference from the acetaminophen. The temporal profile of CGM interference followed acetaminophen concentrations measured in interstitial fluid (ISF). Conclusions: This is the first direct measurement of ISF concentrations of putative CGM interferences with simultaneous measurements of CGM performance in the presence of the interferences. The observed interference with glucose measurements in the tested CGM devices coincided temporally with appearance of acetaminophen in the ISF. The method applied here can be used to determine the susceptibility of current and future CGM systems to interference from acetaminophen or other exogenous pharmacologic agents. PMID:26784129

Glymphatic distribution of CSF-derived apoE into brain is isoform specific and suppressed during sleep deprivation.

PubMed

Achariyar, Thiyagaragan M; Li, Baoman; Peng, Weiguo; Verghese, Philip B; Shi, Yang; McConnell, Evan; Benraiss, Abdellatif; Kasper, Tristan; Song, Wei; Takano, Takahiro; Holtzman, David M; Nedergaard, Maiken; Deane, Rashid

2016-12-08

Apolipoprotein E (apoE) is a major carrier of cholesterol and essential for synaptic plasticity. In brain, it's expressed by many cells but highly expressed by the choroid plexus and the predominant apolipoprotein in cerebrospinal fluid (CSF). The role of apoE in the CSF is unclear. Recently, the glymphatic system was described as a clearance system whereby CSF and ISF (interstitial fluid) is exchanged via the peri-arterial space and convective flow of ISF clearance is mediated by aquaporin 4 (AQP4), a water channel. We reasoned that this system also serves to distribute essential molecules in CSF into brain. The aim was to establish whether apoE in CSF, secreted by the choroid plexus, is distributed into brain, and whether this distribution pattern was altered by sleep deprivation. We used fluorescently labeled lipidated apoE isoforms, lenti-apoE3 delivered to the choroid plexus, immunohistochemistry to map apoE brain distribution, immunolabeled cells and proteins in brain, Western blot analysis and ELISA to determine apoE levels and radiolabeled molecules to quantify CSF inflow into brain and brain clearance in mice. Data were statistically analyzed using ANOVA or Student's t- test. We show that the glymphatic fluid transporting system contributes to the delivery of choroid plexus/CSF-derived human apoE to neurons. CSF-delivered human apoE entered brain via the perivascular space of penetrating arteries and flows radially around arteries, but not veins, in an isoform specific manner (apoE2 > apoE3 > apoE4). Flow of apoE around arteries was facilitated by AQP4, a characteristic feature of the glymphatic system. ApoE3, delivered by lentivirus to the choroid plexus and ependymal layer but not to the parenchymal cells, was present in the CSF, penetrating arteries and neurons. The inflow of CSF, which contains apoE, into brain and its clearance from the interstitium were severely suppressed by sleep deprivation compared to the sleep state. Thus, choroid plexus/CSF provides an additional source of apoE and the glymphatic fluid transporting system delivers it to brain via the periarterial space. By implication, failure in this essential physiological role of the glymphatic fluid flow and ISF clearance may also contribute to apoE isoform-specific disorders in the long term.

A novel insect-specific flavivirus replicates only in Aedes-derived cells and persists at high prevalence in wild Aedes vigilax populations in Sydney, Australia.

PubMed

McLean, Breeanna J; Hobson-Peters, Jody; Webb, Cameron E; Watterson, Daniel; Prow, Natalie A; Nguyen, Hong Duyen; Hall-Mendelin, Sonja; Warrilow, David; Johansen, Cheryl A; Jansen, Cassie C; van den Hurk, Andrew F; Beebe, Nigel W; Schnettler, Esther; Barnard, Ross T; Hall, Roy A

2015-12-01

To date, insect-specific flaviviruses (ISFs) have only been isolated from mosquitoes and increasing evidence suggests that ISFs may affect the transmission of pathogenic flaviviruses. To investigate the diversity and prevalence of ISFs in Australian mosquitoes, samples from various regions were screened for flaviviruses by ELISA and RT-PCR. Thirty-eight pools of Aedes vigilax from Sydney in 2007 yielded isolates of a novel flavivirus, named Parramatta River virus (PaRV). Sequencing of the viral RNA genome revealed it was closely related to Hanko virus with 62.3% nucleotide identity over the open reading frame. PaRV failed to grow in vertebrate cells, with only Aedes-derived mosquito cell lines permissive to replication, suggesting a narrow host range. 2014 collections revealed that PaRV had persisted in A. vigilax populations in Sydney, with 88% of pools positive. Further investigations into its mode of transmission and potential to influence vector competence of A. vigilax for pathogenic viruses are warranted. Copyright © 2015. Published by Elsevier Inc.

An Evaluation of Traffic Management at ISF Academy on Kong Sin Wan Road

NASA Astrophysics Data System (ADS)

Lu, M.

2016-12-01

The ISF Academy, a school with 1500 students, is located on Kong Sin Wan Road. The majority of students from the academy commute to school every morning by private cars, school buses and other public transportation. For the past few years, the school management team has been imposing traffic management regulations to alleviate and minimize traffic congestion in the nearby area. In spite of that, traffic management on Kong Sin Wan Road is fairly limited and inadequate, resulting in congestion at the start and finish of the school day. As a school, we are dedicated to reduce and mitigate the number of private cars and school buses, as well as to control carbon dioxide emissions from the variety of vehicles. In order to implement strategies to make improvements to the current traffic management system, we, as a school, aim to establish a systematic approach to calculate and model the number of private cars, EV cars, plug-in hybrids and school buses flowing near the ISF campus every day, and the number of students on each vehicle. According to the U.S Environmental Protection Agency (EPA), the average annual carbon dioxide emission for a typical passenger vehicle is 4.7 metric tons. By multiplying the average carbon dioxide emission by the number of cars coming to campus every morning, we will gain a better understanding of the amount of carbon dioxide emitted from school vehicles. To extend the research, we will design a survey to investigate and encourage carpooling between families and students who live close, in order to combat and relieve rising traffic congestion and minimize cars crowding the roads. The traffic study project will not only help the school community create a more environment-friendly campus, but also improve the traffic congestion around the school area.

In vivo measurement of apolipoprotein E from the brain interstitial fluid using microdialysis

PubMed Central

2013-01-01

Background The APOE4 allele variant is the strongest known genetic risk factor for developing late-onset Alzheimer’s disease. The link between apolipoprotein E (apoE) and Alzheimer’s disease is likely due in large part to the impact of apoE on the metabolism of amyloid β (Aβ) within the brain. Manipulation of apoE levels and lipidation within the brain has been proposed as a therapeutic target for the treatment of Alzheimer’s disease. However, we know little about the dynamic regulation of apoE levels and lipidation within the central nervous system. We have developed an assay to measure apoE levels in the brain interstitial fluid of awake and freely moving mice using large molecular weight cut-off microdialysis probes. Results We were able to recover apoE using microdialysis from human cerebrospinal fluid (CSF) in vitro and mouse brain parenchyma in vivo. Microdialysis probes were inserted into the hippocampus of wild-type mice and interstitial fluid was collected for 36 hours. Levels of apoE within the microdialysis samples were determined by ELISA. The levels of apoE were found to be relatively stable over 36 hours. No apoE was detected in microdialysis samples from apoE KO mice. Administration of the RXR agonist bexarotene increased ISF apoE levels while ISF Aβ levels were decreased. Extrapolation to zero-flow analysis allowed us to determine the absolute recoverable concentration of apoE3 in the brain ISF of apoE3 KI mice. Furthermore, analysis of microdialysis samples by non-denaturing gel electrophoresis determined lipidated apoE particles in microdialysis samples were consistent in size with apoE particles from CSF. Finally, we found that the concentration of apoE in the brain ISF was dependent upon apoE isoform in human apoE KI mice, following the pattern apoE2>apoE3>apoE4. Conclusions We are able to collect lipidated apoE from the brain of awake and freely moving mice and monitor apoE levels over the course of several hours from a single mouse. Our technique enables assessment of brain apoE dynamics under physiological and pathophysiological conditions and in response to therapeutic interventions designed to affect apoE levels and lipidation within the brain. PMID:23601557

Noninvasive glucose sensing by transcutaneous Raman spectroscopy

NASA Astrophysics Data System (ADS)

Shih, Wei-Chuan; Bechtel, Kate L.; Rebec, Mihailo V.

2015-05-01

We present the development of a transcutaneous Raman spectroscopy system and analysis algorithm for noninvasive glucose sensing. The instrument and algorithm were tested in a preclinical study in which a dog model was used. To achieve a robust glucose test system, the blood levels were clamped for periods of up to 45 min. Glucose clamping and rise/fall patterns have been achieved by injecting glucose and insulin into the ear veins of the dog. Venous blood samples were drawn every 5 min and a plasma glucose concentration was obtained and used to maintain the clamps, to build the calibration model, and to evaluate the performance of the system. We evaluated the utility of the simultaneously acquired Raman spectra to be used to determine the plasma glucose values during the 8-h experiment. We obtained prediction errors in the range of ˜1.5-2 mM. These were in-line with a best-case theoretical estimate considering the limitations of the signal-to-noise ratio estimates. As expected, the transition regions of the clamp study produced larger predictive errors than the stable regions. This is related to the divergence of the interstitial fluid (ISF) and plasma glucose values during those periods. Two key contributors to error beside the ISF/plasma difference were photobleaching and detector drift. The study demonstrated the potential of Raman spectroscopy in noninvasive applications and provides areas where the technology can be improved in future studies.

Noninvasive glucose sensing by transcutaneous Raman spectroscopy.

PubMed

Shih, Wei-Chuan; Bechtel, Kate L; Rebec, Mihailo V

2015-05-01

We present the development of a transcutaneous Raman spectroscopy system and analysis algorithm for noninvasive glucose sensing. The instrument and algorithm were tested in a preclinical study in which a dog model was used. To achieve a robust glucose test system, the blood levels were clamped for periods of up to 45 min. Glucose clamping and rise/fall patterns have been achieved by injecting glucose and insulin into the ear veins of the dog. Venous blood samples were drawn every 5 min and a plasma glucose concentration was obtained and used to maintain the clamps, to build the calibration model, and to evaluate the performance of the system. We evaluated the utility of the simultaneously acquired Raman spectra to be used to determine the plasma glucose values during the 8-h experiment. We obtained prediction errors in the range of ~1.5-2  mM. These were in-line with a best-case theoretical estimate considering the limitations of the signal-to-noise ratio estimates. As expected, the transition regions of the clamp study produced larger predictive errors than the stable regions. This is related to the divergence of the interstitial fluid (ISF) and plasma glucose values during those periods. Two key contributors to error beside the ISF/plasma difference were photobleaching and detector drift. The study demonstrated the potential of Raman spectroscopy in noninvasive applications and provides areas where the technology can be improved in future studies.

Predicting language outcomes for children learning AAC: Child and environmental factors

PubMed Central

Brady, Nancy C.; Thiemann-Bourque, Kathy; Fleming, Kandace; Matthews, Kris

2014-01-01

Purpose To investigate a model of language development for nonverbal preschool age children learning to communicate with AAC. Method Ninety-three preschool children with intellectual disabilities were assessed at Time 1, and 82 of these children were assessed one year later at Time 2. The outcome variable was the number of different words the children produced (with speech, sign or SGD). Children’s intrinsic predictor for language was modeled as a latent variable consisting of cognitive development, comprehension, play, and nonverbal communication complexity. Adult input at school and home, and amount of AAC instruction were proposed mediators of vocabulary acquisition. Results A confirmatory factor analysis revealed that measures converged as a coherent construct and an SEM model indicated that the intrinsic child predictor construct predicted different words children produced. The amount of input received at home but not at school was a significant mediator. Conclusions Our hypothesized model accurately reflected a latent construct of Intrinsic Symbolic Factor (ISF). Children who evidenced higher initial levels of ISF and more adult input at home produced more words one year later. Findings support the need to assess multiple child variables, and suggest interventions directed to the indicators of ISF and input. PMID:23785187

Tuning Singlet Fission in π-Bridge-π Chromophores

DOE PAGES

Kumarasamy, Elango; Sanders, Samuel N.; Tayebjee, Murad J. Y.; ...

2017-08-11

For this study, we have designed a series of pentacene dimers separated by homoconjugated or nonconjugated bridges that exhibit fast and efficient intramolecular singlet exciton fission (iSF). These materials are distinctive among reported iSF compounds because they exist in the unexplored regime of close spatial proximity but weak electronic coupling between the singlet exciton and triplet pair states. Using transient absorption spectroscopy to investigate photophysics in these molecules, we find that homoconjugated dimers display desirable excited-state dynamics, with significantly reduced recombination rates as compared to conjugated dimers with similar singlet fission rates. In addition, unlike conjugated dimers, the time constantsmore » for singlet fission are relatively insensitive to the interplanar angle between chromophores, since rotation about σ bonds negligibly affects the orbital overlap within the π-bonding network. In the nonconjugated dimer, where the iSF occurs with a time constant >10 ns, comparable to the fluorescence lifetime, we used electron spin resonance spectroscopy to unequivocally establish the formation of triplet–triplet multiexcitons and uncoupled triplet excitons through singlet fission. Together, these studies enable us to articulate the role of the conjugation motif in iSF.« less

The Effects of Peripheral and Central High Insulin on Brain Insulin Signaling and Amyloid-β in Young and Old APP/PS1 Mice

PubMed Central

Stanley, Molly; Macauley, Shannon L.; Caesar, Emily E.; Koscal, Lauren J.; Moritz, Will; Robinson, Grace O.; Roh, Joseph; Keyser, Jennifer; Jiang, Hong

2016-01-01

Hyperinsulinemia is a risk factor for late-onset Alzheimer's disease (AD). In vitro experiments describe potential connections between insulin, insulin signaling, and amyloid-β (Aβ), but in vivo experiments are needed to validate these relationships under physiological conditions. First, we performed hyperinsulinemic-euglycemic clamps with concurrent hippocampal microdialysis in young, awake, behaving APPswe/PS1dE9 transgenic mice. Both a postprandial and supraphysiological insulin clamp significantly increased interstitial fluid (ISF) and plasma Aβ compared with controls. We could detect no increase in brain, ISF, or CSF insulin or brain insulin signaling in response to peripheral hyperinsulinemia, despite detecting increased signaling in the muscle. Next, we delivered insulin directly into the hippocampus of young APP/PS1 mice via reverse microdialysis. Brain tissue insulin and insulin signaling was dose-dependently increased, but ISF Aβ was unchanged by central insulin administration. Finally, to determine whether peripheral and central high insulin has differential effects in the presence of significant amyloid pathology, we repeated these experiments in older APP/PS1 mice with significant amyloid plaque burden. Postprandial insulin clamps increased ISF and plasma Aβ, whereas direct delivery of insulin to the hippocampus significantly increased tissue insulin and insulin signaling, with no effect on Aβ in old mice. These results suggest that the brain is still responsive to insulin in the presence of amyloid pathology but increased insulin signaling does not acutely modulate Aβ in vivo before or after the onset of amyloid pathology. Peripheral hyperinsulinemia modestly increases ISF and plasma Aβ in young and old mice, independent of neuronal insulin signaling. SIGNIFICANCE STATEMENT The transportation of insulin from blood to brain is a saturable process relevant to understanding the link between hyperinsulinemia and AD. In vitro experiments have found direct connections between high insulin and extracellular Aβ, but these mechanisms presume that peripheral high insulin elevates brain insulin significantly. We found that physiological hyperinsulinemia in awake, behaving mice does not increase CNS insulin to an appreciable level yet modestly increases extracellular Aβ. We also found that the brain of aged APP/PS1 mice was not insulin resistant, contrary to the current state of the literature. These results further elucidate the relationship between insulin, the brain, and AD and its conflicting roles as both a risk factor and potential treatment. PMID:27852778

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory.

PubMed

Yau, David T W; Wong, May C M; Lam, K F; McGrath, Colman

2015-08-19

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ11-14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ11-14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions. A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions. Both CPQ11-14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic <10 indicated the absence of local dependency. Flat and low IIFs were observed in the oral symptoms items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item "Concerned with what other people think" demonstrated a uniform DIF (p < 0.001). The expected score functions were not much different between boys and girls. Items related to oral symptoms were not informative to OHRQoL and deletion of these items is suggested. The impact of DIF across gender on the overall score was minimal. CPQ11-14 RSF:8 performed slightly better than ISF:8 in measurement precision. The 6-item short forms suggested by IRT validation should be further investigated to ensure their robustness, responsiveness and discriminative performance.

ICESat (GLAS) Science Processing Software Document Series. Volume 2; Science Data Management Plan; 4.0

NASA Technical Reports Server (NTRS)

Jester, Peggy L.; Hancock, David W., III

1999-01-01

This document provides the Data Management Plan for the GLAS Standard Data Software (SDS) supporting the GLAS instrument of the EOS ICESat Spacecraft. The SDS encompasses the ICESat Science Investigator-led Processing System (I-SIPS) Software and the Instrument Support Facility (ISF) Software. This Plan addresses the identification, authority, and description of the interface nodes associated with the GLAS Standard Data Products and the GLAS Ancillary Data.

Alzheimer's disease: a gas model. The NADPH oxidase-Nitric Oxide system as an antibubble biomachinery.

PubMed

Denis, Pierre A

2013-12-01

Alzheimer's disease (AD) is a neurodegenerative disease of unknown origin. The pathological lesions that define AD would be linked to the insidious accumulation of nitrogen, having invaded the brain interstitial fluid (ISF) from the blood via the physiological cycling pool of vascular glucose transporters (GLUT-1). According to this hypothesis, the nitrogen nanobubbles, being chemically inert and actually indestructible for human beings, can not escape from the ISF anymore. They would exert a huge and deleterious pressure against cellular components, especially in microglia and in astrocytes. They could enhance the existing cell oxygen anisotropy, which might enhance the natural bubble nucleation of O2-2O2 in cells or in mitochondria. Indeed, with the help of a new symbolic representation for gas nuclei in chemical reactions, the NADPH oxidase-NO system is identified for the first time, as an antibubble biomachinery, able to break O2-2O2 bubbles up as it releases superoxide O2-. Superoxide is considered as a quantum bubble, which collapses through the reactivity of the gaseous NO radical. Their combination in soluble peroxinitrite provides the change from one state of matter to another, avoiding any risk of a bubble enlargement, and finally avoiding the risk of enzyme crowding or of a bulk pressure variation. However, a bubble is expected to entrap Nitric Oxide (NO), which leads theoretically to a decrease in its bioavailability, and is expected to trigger a guanylyl-cyclase-mediated inflammatory cascade, that could explain the inflammation in AD. In vitro, any increase in the hydrostatic pressure has already been linked to the microtubule disorganization. The amyloid deposits, also known as senile plaques, would behave as a sponge toward ISF nitrogen; Aβ is considered as a foam-stabilizing agent. By taking the shape of cerebral amyloid angiopathy, the amyloid could confine the nitrogen leak from the blood, and progressively insulate the Blood-Brain Barrier against the pollutant. All these theoretical features finally lead to the death of the neurons. The comprehensive statement of the theoretical pro-inflammatory action of inert gases is a real upheaval for the whole medicine. Copyright © 2013 The Author. Published by Elsevier Ltd.. All rights reserved.

Mapping Land and Water Surface Topography with instantaneous Structure from Motion

NASA Astrophysics Data System (ADS)

Dietrich, J.; Fonstad, M. A.

2012-12-01

Structure from Motion (SfM) has given researchers an invaluable tool for low-cost, high-resolution 3D mapping of the environment. These SfM 3D surface models are commonly constructed from many digital photographs collected with one digital camera (either handheld or attached to aerial platform). This method works for stationary or very slow moving objects. However, objects in motion are impossible to capture with one-camera SfM. With multiple simultaneously triggered cameras, it becomes possible to capture multiple photographs at the same time which allows for the construction 3D surface models of moving objects and surfaces, an instantaneous SfM (ISfM) surface model. In river science, ISfM provides a low-cost solution for measuring a number of river variables that researchers normally estimate or are unable to collect over large areas. With ISfM and sufficient coverage of the banks and RTK-GPS control it is possible to create a digital surface model of land and water surface elevations across an entire channel and water surface slopes at any point within the surface model. By setting the cameras to collect time-lapse photography of a scene it is possible to create multiple surfaces that can be compared using traditional digital surface model differencing. These water surface models could be combined the high-resolution bathymetry to create fully 3D cross sections that could be useful in hydrologic modeling. Multiple temporal image sets could also be used in 2D or 3D particle image velocimetry to create 3D surface velocity maps of a channel. Other applications in earth science include anything where researchers could benefit from temporal surface modeling like mass movements, lava flows, dam removal monitoring. The camera system that was used for this research consisted of ten pocket digital cameras (Canon A3300) equipped with wireless triggers. The triggers were constructed with an Arduino-style microcontroller and off-the-shelf handheld radios with a maximum range of several kilometers. The cameras are controlled from another microcontroller/radio combination that allows for manual or automatic triggering of the cameras. The total cost of the camera system was approximately 1500 USD.

Pentacene Dimers as a Critical Tool for the Investigation of Intramolecular Singlet Fission.

PubMed

Hetzer, Constantin; Guldi, Dirk M; Tykwinski, Rik R

2018-01-11

Singlet fission (SF) involves the spontaneous splitting of a photoexcited singlet state into a pair of triplets, and it holds great promise toward the realization of more efficient solar cells. Although the process of SF has been known since the 1960s, debate regarding the underlying mechanism continues to this day, especially for molecular materials. A number of different chromophores have been synthesized and studied in order to better understand the process of SF. These previous reports have established that pentacene and its derivatives are especially well-suited for the study of SF, since the energetic requirement E(S 1 )≥2E(T 1 ) is fulfilled rendering the process exothermic and unidirectional. Dimeric pentacene derivatives, in which individual pentacene chromophores are tethered by a "spacer", have emerged as the system of choice toward exploring the mechanism of intramolecular singlet fission (iSF). The dimeric structure, and in particular the spacer, allows for controlling and tuning the distance, geometric relationship, and electronic coupling between the two pentacene moieties. This Minireview describes recent advances using pentacene dimers for the investigation of iSF. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Persistent Iliosacral Joint Syndrome following Instrumentation to the Sacropelvis in Patients with Adult Spinal Deformity.

PubMed

Diesing, Daniela; Franke, Joerg; Tschoeke, Sven Kevin; Schultheiß, Rolf; Scheufler, Kai Michael

2018-05-31

 Persistent sacroiliac joint syndrome (PSIJS) may complicate adult spinal deformity surgery (ASDS). This study assesses the relationship between clinical/morphometric parameters and PSIJS following ASDS including pelvic fixation and the therapeutic efficacy of secondary iliosacral fusion (ISF).  Perioperative health-related quality of life (HRQOL) outcomes (Oswestry Disability Index, Short Form 12-item health survey, version 2 scores) at 6, 12, and 24 months, and radiographic studies were analyzed retrospectively in a cohort of 71 consecutive patients undergoing ASDS. PSIJS was confirmed in nine individuals (12.7%) by placebo-controlled dual sacroiliac joint (SIJ) blocks. The relationships between global and regional spinopelvic morphometry, PSIJS, and HRQOL outcomes were assessed by logistic regression and receiver operating characteristic curve (ROC) analysis.  PSIJS, independently causing significantly reduced improvement in HRQOL scores ( p  < 0.001) 6 months postoperatively, warranted secondary ISF in nine patients (12.7%) within 12 months of index surgery, without evidence of progressive SIJ arthrosis, pseudarthrosis, or hardware issues. Eight of nine patients undergoing secondary ISF reported≥ 70% pain reduction at 24 months. Logistic regression/ROC analysis revealed a close association between PSIJS and nonharmonious postoperative L4-S1 fractional lordosis ( p  < 0.0001), pelvic incidence angle > 53 degrees, hip arthrosis, and preexistent advanced SIJ arthrosis ( p  < 0.01).  PSIJS may negatively impact the clinical outcome of ASDS. Recurrent preoperative SIJ syndrome requiring interventional treatment, preexisting hip and SIJ arthrosis, insufficient restoration of L4-S1 fractional lordosis, and high pelvic incidence predispose to PSIJS. PSIJS may potentially be avoided by restoring physiologic lumbosacral geometry and S2 sacral alar-iliac screw fixation during index surgery. Secondary ISF appears to be effective in reducing pain and physical impairment due to PSIJS. Georg Thieme Verlag KG Stuttgart · New York.

Visualisation and quantification of heavy metal accessibility in smelter slags: The influence of morphology on availability.

PubMed

Morrison, Anthony L; Swierczek, Zofia; Gulson, Brian L

2016-03-01

The Imperial Smelting Furnace (ISF) for producing lead and zinc simultaneously has operated on four continents and in eleven countries from the 1950's. One of the process changes that the ISF introduced was the production of a finely granulated slag waste. Although this slag contained significant amounts of residual lead (Pb) and zinc (Zn), because of its glassy nature it was considered environmentally benign. From the Cockle Creek smelter near Boolaroo at the northern end of Lake Macquarie, NSW, Australia, it is estimated that around 2.1 million tonnes of the fine slag was distributed into the community and most remains where it was originally utilised. Residual tonnages of slag of this magnitude are common worldwide wherever the ISF operated. Studies of base metal smelting slags have concluded that mineralogical and morphological characteristics of the slag play a critical role in moderating environmental release of toxic elements. Scanning electron microscopy (SEM) and microanalysis of the ISF slags has shown that the Pb and associated elements are present as discrete nodules (∼6-22 μm) in the slag and that they are not associated with Zn which is contained in the glass slag phase. Using an automated SEM and analysis technique (QEMSCAN(®)) to "map" the mineralogical structure of the particles, it was possible to quantitatively determine the degree of access infiltrating fluids might have to the reaction surface of the Pb phases. The level of access decreases with increasing particle size, but in even the largest sized particles (-3350 + 2000 μm) nearly 80% of the Pb-containing phases were totally or partially accessible. These results provide evidence that the toxic elements in the slags are not contained by the glassy phase and will be vulnerable to leaching over time depending on their individual phase reactivity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy Tracking in Classrooms - A Real Time Experiment with Grade 5 Students

NASA Astrophysics Data System (ADS)

Lam, H. M.; Ho, F.

2015-12-01

ISF Academy, a K-G12 school in Hong Kong with over 1500 students and currently spanning 3 buildings, is retrofitting the school with an energy tracking system in three phases. The first phase during the fall of 2015 will include retrofitting eight Grade 5 classrooms. This new program will show the daily energy usage data from these classrooms. The Grade 5 students receive feedback on their energy use in real time as they compete over two months in their homeroom classes to lower their electrical use, and subsequently their carbon footprint. This competition style initiative will teach the 180 Grade 5 students about their energy usage in a fun and informative manner. ISF Academy has over 400 air-conditioners and we have already determined that the air conditioners are the largest single use of energy in the school. The energy tracking system installed and maintained by from Global Design Corporation utilizes uniquely identified current detectors attached to circuit breakers, to monitor electrical use of individual circuits. These detectors will also monitor the energy used for classroom lighting, fans and plugs, as well as the air conditioners. The system has been installed and the Grade 5 classrooms averaged between 40 kWh and 120 kWh of usage in May 2015. This data will be used as the baseline for the competition. Further analysis can also be done with the data, such as calculating the carbon emissions reduction throughout the school year, providing possible class learning activities and also aiding in future energy use and carbon footprint predictions. The data collected will help refine phase 2 and 3 of the installation, expanding the system to more buildings and also giving insight to the rollout of the system to the whole school when the systems are fully in place.

Installation of a Roof Mounted Photovoltaic System

NASA Astrophysics Data System (ADS)

Lam, M.

2015-12-01

In order to create a safe and comfortable environment for students to learn, a lot of electricity, which is generated from coal fired power plants, is used. Therefore, ISF Academy, a school in Hong Kong with approximately 1,500 students, will be installing a rooftop photovoltaic (PV) system with 302 solar panels. Not only will these panels be used to power a classroom, they will also serve as an educational opportunity for students to learn about the importance of renewable energy technology and its uses. There were four different options for the installation of the solar panels, and the final choice was made based on the loading capacity of the roof, considering the fact that overstressing the roof could prove to be a safety hazard. Moreover, due to consideration of the risk of typhoons in Hong Kong, the solar panel PV system will include concrete plinths as counterweights - but not so much that the roof would be severely overstressed. During and after the installation of the PV system, students involved would be able to do multiple calculations, such as determining the reduction of the school's carbon footprint. This can allow students to learn about the impact renewable energy can have on the environment. Another project students can participate in includes measuring the efficiency of the solar panels and how much power can be produced per year, which in turn can help with calculate the amount of money saved per year and when we will achieve economic parity. In short, the installation of the roof mounted PV system will not only be able to help save money for the school but also provide learning opportunities for students studying at the ISF Academy.

Multiplicity of cerebrospinal fluid functions: New challenges in health and disease

PubMed Central

Johanson, Conrad E; Duncan, John A; Klinge, Petra M; Brinker, Thomas; Stopa, Edward G; Silverberg, Gerald D

2008-01-01

This review integrates eight aspects of cerebrospinal fluid (CSF) circulatory dynamics: formation rate, pressure, flow, volume, turnover rate, composition, recycling and reabsorption. Novel ways to modulate CSF formation emanate from recent analyses of choroid plexus transcription factors (E2F5), ion transporters (NaHCO3 cotransport), transport enzymes (isoforms of carbonic anhydrase), aquaporin 1 regulation, and plasticity of receptors for fluid-regulating neuropeptides. A greater appreciation of CSF pressure (CSFP) is being generated by fresh insights on peptidergic regulatory servomechanisms, the role of dysfunctional ependyma and circumventricular organs in causing congenital hydrocephalus, and the clinical use of algorithms to delineate CSFP waveforms for diagnostic and prognostic utility. Increasing attention focuses on CSF flow: how it impacts cerebral metabolism and hemodynamics, neural stem cell progression in the subventricular zone, and catabolite/peptide clearance from the CNS. The pathophysiological significance of changes in CSF volume is assessed from the respective viewpoints of hemodynamics (choroid plexus blood flow and pulsatility), hydrodynamics (choroidal hypo- and hypersecretion) and neuroendocrine factors (i.e., coordinated regulation by atrial natriuretic peptide, arginine vasopressin and basic fibroblast growth factor). In aging, normal pressure hydrocephalus and Alzheimer's disease, the expanding CSF space reduces the CSF turnover rate, thus compromising the CSF sink action to clear harmful metabolites (e.g., amyloid) from the CNS. Dwindling CSF dynamics greatly harms the interstitial environment of neurons. Accordingly the altered CSF composition in neurodegenerative diseases and senescence, because of adverse effects on neural processes and cognition, needs more effective clinical management. CSF recycling between subarachnoid space, brain and ventricles promotes interstitial fluid (ISF) convection with both trophic and excretory benefits. Finally, CSF reabsorption via multiple pathways (olfactory and spinal arachnoidal bulk flow) is likely complemented by fluid clearance across capillary walls (aquaporin 4) and arachnoid villi when CSFP and fluid retention are markedly elevated. A model is presented that links CSF and ISF homeostasis to coordinated fluxes of water and solutes at both the blood-CSF and blood-brain transport interfaces. Outline 1 Overview 2 CSF formation 2.1 Transcription factors 2.2 Ion transporters 2.3 Enzymes that modulate transport 2.4 Aquaporins or water channels 2.5 Receptors for neuropeptides 3 CSF pressure 3.1 Servomechanism regulatory hypothesis 3.2 Ontogeny of CSF pressure generation 3.3 Congenital hydrocephalus and periventricular regions 3.4 Brain response to elevated CSF pressure 3.5 Advances in measuring CSF waveforms 4 CSF flow 4.1 CSF flow and brain metabolism 4.2 Flow effects on fetal germinal matrix 4.3 Decreasing CSF flow in aging CNS 4.4 Refinement of non-invasive flow measurements 5 CSF volume 5.1 Hemodynamic factors 5.2 Hydrodynamic factors 5.3 Neuroendocrine factors 6 CSF turnover rate 6.1 Adverse effect of ventriculomegaly 6.2 Attenuated CSF sink action 7 CSF composition 7.1 Kidney-like action of CP-CSF system 7.2 Altered CSF biochemistry in aging and disease 7.3 Importance of clearance transport 7.4 Therapeutic manipulation of composition 8 CSF recycling in relation to ISF dynamics 8.1 CSF exchange with brain interstitium 8.2 Components of ISF movement in brain 8.3 Compromised ISF/CSF dynamics and amyloid retention 9 CSF reabsorption 9.1 Arachnoidal outflow resistance 9.2 Arachnoid villi vs. olfactory drainage routes 9.3 Fluid reabsorption along spinal nerves 9.4 Reabsorption across capillary aquaporin channels 10 Developing translationally effective models for restoring CSF balance 11 Conclusion PMID:18479516

MEANS 2: Microstructure- and Micromechanism-Sensitive Property Models for Advanced Turbine Disk and Blade Systems

DTIC Science & Technology

2009-12-31

f„„„,„ -L...-J..— - —I 1 / f+_—=p / —j \\-\\- 4A 14 4A»4 / 4A C4 M / »4.4C A4, «i »A OWOLC $-ISF s - csr !•» ’ML...Materials Society) Publications. 23. S . Ma, L. Carroll and T.M. Pollock, "Development of y Phase Stacking Faults during High Temperature Creep of Ru...into the design of advanced disk and blade systems 6. AUTHOR( S ) Michael J Mills 5. FUNDING NUMBERS FA9550-05-1-0135 7. PERFORMING ORGANIZATION

Visual discomfort while watching stereoscopic three-dimensional movies at the cinema.

PubMed

Zeri, Fabrizio; Livi, Stefano

2015-05-01

This study investigates discomfort symptoms while watching Stereoscopic three-dimensional (S3D) movies in the 'real' condition of a cinema. In particular, it had two main objectives: to evaluate the presence and nature of visual discomfort while watching S3D movies, and to compare visual symptoms during S3D and 2D viewing. Cinema spectators of S3D or 2D films were interviewed by questionnaire at the theatre exit of different multiplex cinemas immediately after viewing a movie. A total of 854 subjects were interviewed (mean age 23.7 ± 10.9 years; range 8-81 years; 392 females and 462 males). Five hundred and ninety-nine of them viewed different S3D movies, and 255 subjects viewed a 2D version of a film seen in S3D by 251 subjects from the S3D group for a between-subjects design for that comparison. Exploratory factor analysis revealed two factors underlying symptoms: External Symptoms Factors (ESF) with a mean ± S.D. symptom score of 1.51 ± 0.58 comprised of eye burning, eye ache, eye strain, eye irritation and tearing; and Internal Symptoms Factors (ISF) with a mean ± S.D. symptom score of 1.38 ± 0.51 comprised of blur, double vision, headache, dizziness and nausea. ISF and ESF were significantly correlated (Spearman r = 0.55; p = 0.001) but with external symptoms significantly higher than internal ones (Wilcoxon Signed-ranks test; p = 0.001). The age of participants did not significantly affect symptoms. However, females had higher scores than males for both ESF and ISF, and myopes had higher ISF scores than hyperopes. Newly released movies provided lower ESF scores than older movies, while the seat position of spectators had minimal effect. Symptoms while viewing S3D movies were significantly and negatively correlated to the duration of wearing S3D glasses. Kruskal-Wallis results showed that symptoms were significantly greater for S3D compared to those of 2D movies, both for ISF (p = 0.001) and for ESF (p = 0.001). In short, the analysis of the symptoms experienced by S3D movie spectators based on retrospective visual comfort assessments, showed a higher level of external symptoms (eye burning, eye ache, tearing, etc.) when compared to the internal ones that are typically more perceptual (blurred vision, double vision, headache, etc.). Furthermore, spectators of S3D movies reported statistically higher symptoms when compared to 2D spectators. © 2015 The Authors Ophthalmic & Physiological Optics © 2015 The College of Optometrists.

Thermomechanical simulations and experimental validation for high speed incremental forming

NASA Astrophysics Data System (ADS)

Ambrogio, Giuseppina; Gagliardi, Francesco; Filice, Luigino; Romero, Natalia

2016-10-01

Incremental sheet forming (ISF) consists in deforming only a small region of the workspace through a punch driven by a NC machine. The drawback of this process is its slowness. In this study, a high speed variant has been investigated from both numerical and experimental points of view. The aim has been the design of a FEM model able to perform the material behavior during the high speed process by defining a thermomechanical model. An experimental campaign has been performed by a CNC lathe with high speed to test process feasibility. The first results have shown how the material presents the same performance than in conventional speed ISF and, in some cases, better material behavior due to the temperature increment. An accurate numerical simulation has been performed to investigate the material behavior during the high speed process confirming substantially experimental evidence.

Interfacial spin-filter assisted spin transfer torque effect in Co/BeO/Co magnetic tunnel junction

NASA Astrophysics Data System (ADS)

Tang, Y.-H.; Chu, F.-C.

2015-03-01

The first-principles calculation is employed to demonstrate the spin-selective transport properties and the non-collinear spin-transfer torque (STT) effect in the newly proposed Co/BeO/Co magnetic tunnel junction. The subtle spin-polarized charge transfer solely at O/Co interface gives rise to the interfacial spin-filter (ISF) effect, which can be simulated within the tight binding model to verify the general expression of STT. This allows us to predict the asymmetric bias behavior of non-collinear STT directly via the interplay between the first-principles calculated spin current densities in collinear magnetic configurations. We believe that the ISF effect, introduced by the combination between wurtzite-BeO barrier and the fcc-Co electrode, may open a new and promising route in semiconductor-based spintronics applications.

Functional Polarity of Microvascular Brain Endothelial Cells Supported by Neurovascular Unit Computational Model of Large Neutral Amino Acid Homeostasis

PubMed Central

Taslimifar, Mehdi; Buoso, Stefano; Verrey, Francois; Kurtcuoglu, Vartan

2018-01-01

The homeostatic regulation of large neutral amino acid (LNAA) concentration in the brain interstitial fluid (ISF) is essential for proper brain function. LNAA passage into the brain is primarily mediated by the complex and dynamic interactions between various solute carrier (SLC) transporters expressed in the neurovascular unit (NVU), among which SLC7A5/LAT1 is considered to be the major contributor in microvascular brain endothelial cells (MBEC). The LAT1-mediated trans-endothelial transport of LNAAs, however, could not be characterized precisely by available in vitro and in vivo standard methods so far. To circumvent these limitations, we have incorporated published in vivo data of rat brain into a robust computational model of NVU-LNAA homeostasis, allowing us to evaluate hypotheses concerning LAT1-mediated trans-endothelial transport of LNAAs across the blood brain barrier (BBB). We show that accounting for functional polarity of MBECs with either asymmetric LAT1 distribution between membranes and/or intrinsic LAT1 asymmetry with low intraendothelial binding affinity is required to reproduce the experimentally measured brain ISF response to intraperitoneal (IP) L-tyrosine and L-phenylalanine injection. On the basis of these findings, we have also investigated the effect of IP administrated L-tyrosine and L-phenylalanine on the dynamics of LNAAs in MBECs, astrocytes and neurons. Finally, the computational model was shown to explain the trans-stimulation of LNAA uptake across the BBB observed upon ISF perfusion with a competitive LAT1 inhibitor. PMID:29593549

Update on Mathematical Modeling Research to Support the Development of Automated Insulin Delivery Systems

DTIC Science & Technology

2010-05-01

that believed the delay is ≤10–15 min, 50% believed that insulin can cause changes in the blood (i.e., plasma)-to-ISF glucose gradient. Also, 50% still...by the R01HL88448-1 grant, which seeks to establish safe pediatric euglycemia after cardiac surgery in neonates using continuous glucose monitoring...2062–7. 9. Burge MR, Castillo KR, Schade DS. Meal composition is a determinant of lispro-induced hypoglycemia in IDDM. Diabetes Care. 1997;20(2):152–5

Evaluation of Experiential Outdoor Research Locations in Asia for a K-12 school in Hong Kong

NASA Astrophysics Data System (ADS)

Ibarra, D. L.; Joyce, S.

2016-12-01

A team of faculty and administrators from The Independent Schools Foundation Academy spend the 2015 - 2016 academic year identifying possible locations in Asia for a year-round outdoor education center. ISF Academy currently has over 1500 students its K-12 bilingual school in Hong Kong, China. The outdoor education center is an extension of the built campus in Pokfulam and will provide students opportunities to live in a natural setting, participate in outdoor educational activities and study in an environment significantly different than a classroom. Currently ISF Academy students in grades 4 - 12 are off campus twice during the academic year in an experiential learning environment. These current programs include camping, hiking, kayaking, other adventurous activities and service learning opportunities. The purpose of the dedicated site is to have a "home base" for ISF Academy and the experiential learning programs. This past year we looked specifically at programs and locations that could also be used by students for ecology and earth systems based research in the senior school (grades 9 - 12). We have looked at sites in Hong Kong, Indonesia, Malaysia and Taiwan. The ideal site will have marine, terrestrial and mangrove ecosystems and allow students to set up long-term research sites in any of these ecosystems. Creating opportunities for authentic research that allows students spend an extended time in a research setting will help them to gain both skills and independence needed in the future at the tertiary level. The evaluation of these sites included identifying potential research partners, site preparation, logistics in and out of the locations, and the heath/safety management of students living and working in a remote location. In parallel to the site evaluations, the curriculum is being developed for the students that is age and skill appropriate using the frame work of the existing guided discovery curriculum in the primary school, and the MYP and DP curriculum of the IBO for the secondary school. Delivering a curriculum of this complexity will require participation and input from faculty across all disciplines.

Replace with abstract title

NASA Astrophysics Data System (ADS)

Coho, Aleksander; Kioussis, Nicholas

2003-03-01

We use the semidiscrete variational generelized Peierls-Nabarro model to study the effect of Cu alloying on the dislocation properties of Al. First-principles density functional theory (DFT) is used to calculate the generalized-stacking-fault (GSF) energy surface when a <111> plane, on which one in four Al atoms has been replaced with a Cu atom, slips over a pure Al <111> plane. Various dislocation core properties (core width, energy, Peierls stress, dissociation tendency) are investigated and compared with the pure Al case. Cu alloying lowers the intrinsic stacking fault (ISF) energy, which makes dislocations more likely to dissociate into partials. We also try to understand the lowering of ISF energy in terms of Al-Cu and Al-Al bond formation and braking during shearing along the <112> direction. From the above we draw conclusions about the effects of Cu alloying on the mechanical properties of Al.

Clearing Extracellular Alpha-Synuclein from Cerebrospinal Fluid: A New Therapeutic Strategy in Parkinson’s Disease

PubMed Central

Padilla-Zambrano, Huber S.; Tomás-Zapico, Cristina; García, Benjamin Fernández

2018-01-01

This concept article aims to show the rationale of targeting extracellular α-Synuclein (α-Syn) from cerebrospinal fluid (CSF) as a new strategy to remove this protein from the brain in Parkinson’s disease (PD). Misfolding and intracellular aggregation of α-synuclein into Lewy bodies are thought to be crucial in the pathogenesis of PD. Recent research has shown that small amounts of monomeric and oligomeric α-synuclein are released from neuronal cells by exocytosis and that this extracellular alpha-synuclein contributes to neurodegeneration, progressive spreading of alpha-synuclein pathology, and neuroinflammation. In PD, extracellular oligomeric-α-synuclein moves in constant equilibrium between the interstitial fluid (ISF) and the CSF. Thus, we expect that continuous depletion of oligomeric-α-synuclein in the CSF will produce a steady clearance of the protein in the ISF, preventing transmission and deposition in the brain. PMID:29570693

Clearing Extracellular Alpha-Synuclein from Cerebrospinal Fluid: A New Therapeutic Strategy in Parkinson's Disease.

PubMed

Menéndez-González, Manuel; Padilla-Zambrano, Huber S; Tomás-Zapico, Cristina; García, Benjamin Fernández

2018-03-23

This concept article aims to show the rationale of targeting extracellular α-Synuclein (α-Syn) from cerebrospinal fluid (CSF) as a new strategy to remove this protein from the brain in Parkinson's disease (PD). Misfolding and intracellular aggregation of α-synuclein into Lewy bodies are thought to be crucial in the pathogenesis of PD. Recent research has shown that small amounts of monomeric and oligomeric α-synuclein are released from neuronal cells by exocytosis and that this extracellular alpha-synuclein contributes to neurodegeneration, progressive spreading of alpha-synuclein pathology, and neuroinflammation. In PD, extracellular oligomeric-α-synuclein moves in constant equilibrium between the interstitial fluid (ISF) and the CSF. Thus, we expect that continuous depletion of oligomeric-α-synuclein in the CSF will produce a steady clearance of the protein in the ISF, preventing transmission and deposition in the brain.

STEM Beyond The Classroom: Creating Authentic Outreach Programs That Build Bridges Between The Classroom And Real World Challenges

NASA Astrophysics Data System (ADS)

Ibarra, D. L.; Forder, S. E.; Pritchard, M.

2014-12-01

The ISF Academy was founded by Charles Kao, a Nobel Prize laureate. In 2011, the Shuyuan programs were established at The ISF Academy to operate both as a "school within a school" and as a "school outside the classroom." The Shuyuan programs work together with the IBO Science and Technology subject areas to develop comprehensive and challenging opportunities that address the 14 Grand Engineering Challenges. The goal is to establish co-curricular programs that go beyond the taught curriculum and support STEM curricula. Several programs outside of the classroom include an onsite robotics researcher, underwater and land based robotics programs, field trips, whole school food waste composting and the implementation of an energy tracking system. Relationships with several local universities allow students to work closely with professors in research settings and, annually, a leading researcher gives a keynote speech to our students. Other signature Shuyuan programs have developed international strategic relationships with the NRI at Cambridge University, where students spend several weeks studying science and civilization in China using primary source materials. Additionally, Shuyuan has supported extension opportunities for classroom teachers with institutional partnerships that include the British Council, governmental organizations, local universities, corporations, and NGOs. In conclusion, the overall goal of the Shuyuan Programs is to provide experiential learning opportunities that challenge conventional curriculum design in a manner that is supportive and innovative!

Isolation of a Novel Insect-Specific Flavivirus from Culiseta melanura in the Northeastern United States

PubMed Central

Misencik, Michael J.; Grubaugh, Nathan D.; Andreadis, Theodore G.; Ebel, Gregory D.

2016-01-01

Abstract The genus Flavivirus includes a number of newly recognized viruses that infect and replicate only within mosquitoes. To determine whether insect-specific flaviviruses (ISFs) may infect Culiseta (Cs.) melanura mosquitoes, we screened pools of field-collected mosquitoes for virus infection by RT-PCR targeting conserved regions of the NS5 gene. NS5 nucleotide sequences amplified from Cs. melanura pools were genetically similar to other ISFs and most closely matched Calbertado virus from Culex tarsalis, sharing 68.7% nucleotide and 76.1% amino acid sequence identity. The complete genome of one virus isolate was sequenced to reveal a primary open reading frame (ORF) encoding a viral polyprotein characteristic of the genus Flavivirus. Phylogenetic analysis showed that this virus represents a distinct evolutionary lineage that belongs to the classical ISF group. The virus was detected solely in Cs. melanura pools, occurred in sampled populations from Connecticut, New York, New Hampshire, and Maine, and infected both adult and larval stages of the mosquito. Maximum likelihood estimate infection rates (MLE-IR) were relatively stable in overwintering Cs. melanura larvae collected monthly from November of 2012 through May of 2013 (MLE-IR = 0.7–2.1/100 mosquitoes) and in host-seeking females collected weekly from June through October of 2013 (MLE-IR = 3.8–11.5/100 mosquitoes). Phylogenetic analysis of viral sequences revealed limited genetic variation that lacked obvious geographic structure among strains in the northeastern United States. This new virus is provisionally named Culiseta flavivirus on the basis of its host association with Cs. melanura. PMID:26807512

Shear-Induced Amyloid Formation in the Brain: I. Potential Vascular and Parenchymal Processes.

PubMed

Trumbore, Conrad N

2016-09-06

Shear distortion of amyloid-beta (Aβ) solutions accelerates amyloid cascade reactions that may yield different toxic oligomers than those formed in quiescent solutions. Recent experiments indicate that cerebrospinal fluid (CSF) and interstitial fluid (ISF) containing Aβ flow through narrow brain perivascular pathways and brain parenchyma. This paper suggests that such flow causes shear distortion of Aβ molecules involving conformation changes that may be one of the initiating events in the etiology of Alzheimer's disease. Aβ shearing can occur in or around brain arteries and arterioles and is suggested as the origin of cerebral amyloid angiopathy deposits in cerebrovascular walls. Comparatively low flow rates of ISF within the narrow extracellular spaces (ECS) of the brain parenchyma are suggested as a possible initiating factor in both the formation of neurotoxic Aβ42 oligomers and amyloid fibrils. Aβ42 in slow-flowing ISF can gain significant shear energy at or near the walls of tortuous brain ECS flow paths, promoting the formation of a shear-distorted, excited state hydrophobic Aβ42* conformation. This Aβ42* molecule could possibly be involved in one of two paths, one involving rapid adsorption to a brain membrane surface, ultimately forming neurotoxic oligomers on membranes, and the other ultimately forming plaque within the ECS flow pathways. Rising Aβ concentrations combined with shear at or near critical brain membranes are proposed as contributing factors to Alzheimer's disease neurotoxicity. These hypotheses may be applicable in other neurodegenerative diseases, including tauopathies and alpha-synucleinopathies, in which shear-distorted proteins also may form in the brain ECS.

[The receptorial responsiveness method (RRM): a new possibility to estimate the concentration of pharmacologic agonists at their receptors].

PubMed

Pák, Krisztián; Kiss, Zsuzsanna; Erdei, Tamás; Képes, Zita; Gesztelyi, Rudolf

2014-01-01

Cardiovascular disease is the biggest challenge in terms of life expectancy in developed countries. Adenosine contributes to the adaptation of the heart to ischemia and hypoxia, because adenosine, in addition to its metabolite role in the nucleic acid metabolism, is the endogenous agonist of the ubiquitous adenosine receptor family. Adenosine receptor activation is beneficial in most cases, it improves the balance between energy supply and consumption, reduces injury caused by stressors and inhibits the unfavorable tissue remodeling. Pharmacological manipulation of cardioprotective effects evoked by adenosine is an important, although to date not sufficiently utilized endeavor that may have therapeutic and preventive implications in cardiovascular diseases. As the ligand binding site of adenosine receptors is accessible from the extracellular space, it is especially important to know the adenosine concentration of the interstitial fluid ([Ado](ISF)). However, in the functioning heart, [Ado](ISF) values range in an extremely wide interval, spanning from nano- to micromolar concentrations, as estimated by the commonly used methods. Our recently developed procedure, the receptorial responsiveness method (RRM), may resolve this problem in certain cases. RRM enables quantification of an acute increase in the concentration of a pharmacological agonist, uniquely in the microenvironment of the receptors of the given agonist. As a limitation, concentration of agonists with short half-life (just like adenosine) at their receptors can only be quantified with the equieffective concentration of a stable agonist exerting the same action. In a previous study using RRM, inhibition of the transmembrane nucleoside transport in the euthyroid guinea pig atrium produced an increase in [Ado](ISF) that was equieffective with 18.8 +/- 3 nM CPA (N6-cyclopentyladenosine, a stable, selective A1 adenosine receptor agonist). This finding is consistent with observations of others, i.e., in the normoxic heart, adenosine flow is directed into the cell interior, and thus transport blockade elevates the extracellular adenosine level. In turn, nucleoside transport inhibition in the hyperthyroid guinea pig atrium caused a rise in [Ado](ISF) equieffective with 46.5 +/- 13.7 nM CPA. In sum, our work team was the first to demonstrate that adenosine transport in the hyperthyroid atrium has the same direction but is more intense as/than that in the euthyroid one.

Design and Validation Testing of TruckScan to Assay Large Sacks of Fukushima Radioactive Debris on a Truck

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

Suzuki, Atsuo; Bronson, Frazier

As a result of the March 2011 earthquake and resulting tsunami in Japan, there was a serious accident at the Fukushima Dai-ichi Nuclear Power Plant. This accident has contaminated soil and vegetation in a wide area around the plant. Decontamination projects over the last 4 years have resulted in large numbers of 1 cubic meter canvas bags of debris, commonly called Super Sacks [SS]. These are currently stored nearby where they were generated, but starting in 2015, they will be moved to various Interim Storage Facilities [ISF]. Trucks will typically carry 8-20 of these SSs. When the trucks arrive atmore » the ISF they need to be rapidly sorted into groups according to radioactivity level, for efficient subsequent processing. Canberra Industries, Inc. [CI] has designed a new truck monitoring system 'TruckScan' for use at these ISFs. The TruckScan system must measure the entire truck loaded with multiple closely packed SSs, and generate a nuclide specific assay report showing the radioactivity in each individual SS. The Canberra-Japan office, along with Obayashi Corporation have performed validation testing to demonstrate to the regulatory authorities that the proposed technique was sufficiently accurate. These validation tests were conducted at a temporary storage area in Fukushima prefecture. Decontaminated waste of various representative types and of various levels of radioactivity was gathered and mixed to create homogeneous volumes. These volumes were sampled multiple times and assayed with laboratory HPGe detectors to determine the reference concentration of each pile. Multiple SSs were loaded from each pile. Some of the SSs were filled 50% full, others 75% full, and others 100% full, to represent the typical loading configuration of the existing SSs in the field. The content of the SSs are either sand, soil, or vegetation with densities ranging from 0.3 g/cc - 1.6 g/cc. These SSs with known concentrations of Cs-134 and Cs-137 were then loaded onto trucks in a variety of configurations, typical of how they might be on the real trucks. A partial system was installed at the site and used to assay these trucks with the various loading configurations. Whereas the full system will have 8 collimated 3 x 3'' NaI detectors, the test system only had two detectors; therefore the truck was moved and counted 4 times. The data were acquired and analyzed with the Canberra Genie software to determine the peak counts for both Cesium nuclides. That data was then analyzed with a prototype version of a Maximum Entropy algorithm, to determine the individual SS activity. The goal of the validation tests was to demonstrate that the system could detect 1000 Bq/kg in 15 seconds, and to determine how accurately it could quantify individual SSs. The validation tests demonstrated that the product would perform as predicted. The TruckScan results were consistent with the sample assay results [y = 1.0029 x, R{sup 2} = 0.914]. The Total Propagated Uncertainty, including both uncertainties from these tests and others that were estimated but not tested was 16.6% percent. (authors)« less

Acute Effects of Muscarinic M1 Receptor Modulation on AβPP Metabolism and Amyloid-β Levels in vivo: A Microdialysis Study.

PubMed

Welt, Tobias; Kulic, Luka; Hoey, Sarah E; McAfoose, Jordan; Späni, Claudia; Chadha, Antonella Santuccione; Fisher, Abraham; Nitsch, Roger M

2015-01-01

Indirect modulation of cholinergic activity by cholinesterase inhibition is currently a widely established symptomatic treatment for Alzheimer's disease (AD). Selective activation of certain muscarinic receptor subtypes has emerged as an alternative cholinergic-based amyloid-lowering strategy for AD, as selective muscarinic M1 receptor agonists can reduce amyloid-β (Aβ) production by shifting endoproteolytic amyloid-β protein precursor (AβPP) processing toward non-amyloidogenic pathways. In this study, we addressed the hypothesis that acute stimulation of muscarinic M1 receptors can inhibit Aβ production in awake and freely moving AβPP transgenic mice. By combining intracerebral microdialysis with retrodialysis, we determined hippocampal Aβ concentrations during simultaneous pharmacological modulation of brain M1 receptor function. Infusion with a M1 receptor agonist AF102B resulted in a rapid reduction of interstitial fluid (ISF) Aβ levels while treatment with the M1 antagonist dicyclomine increased ISF Aβ levels reaching significance within 120 minutes of treatment. The reduction in Aβ levels was associated with PKCα and ERK activation resulting in increased levels of the α-secretase ADAM17 and a shift in AβPP processing toward the non-amyloidogenic processing pathway. In contrast, treatment with the M1 receptor antagonist dicyclomine caused a decrease in levels of phosphorylated ERK that was independent of PKCα, and led to an elevation of β-secretase levels associated with increased amyloidogenic AβPP processing. The results of this study demonstrate rapid effects of in vivo M1 receptor modulation on the ISF pool of Aβ and suggest that intracerebral microdialysis with retrodialysis is a useful technical approach for monitoring acute treatment effects of muscarinic receptor modulators on AβPP/Aβ metabolism.

Suicide inactivation of cytochrome P-450 by methoxsalen. Evidence for the covalent binding of a reactive intermediate to the protein moiety

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

Labbe, G.; Descatoire, V.; Beaune, P.

Incubation of rat liver microsomes with (3H)methoxsalen and NADPH resulted in the covalent binding of a methoxsalen intermediate to proteins comigrating with cytochromes P-450 UT-A, PB-B/D, ISF-G and PCN-E. Binding was increased by pretreatments with phenobarbital, beta-naphthoflavone (beta NF) and dexamethasone. Such pretreatments also increased the loss of CO-binding capacity either after administration of methoxsalen, or after incubation of hepatic microsomes with methoxsalen and NADPH. Immunoprecipitation of the methoxsalen metabolite-protein adducts in phenobarbital-induced microsomes was moderate with anti-UT-A antibodies, but marked with anti-PB-B/D and anti-PCN-E antibodies. Immunoprecipitation was observed also with anti-ISF-G (anti-beta NF-B) antibodies in beta NF-induced microsomes. Methoxsalenmore » (0.25 mM) inhibited markedly the benzphetamine demethylase activity of phenobarbital-induced microsomes and the erythromycin demethylase activity of dexamethasone-induced microsomes. Whereas methoxsalen itself did not produce any binding spectrum, in contrast either in vivo administration of methoxsalen or incubation in vitro with methoxsalen and NADPH resulted in a low-to-high spin conversion of cytochrome P-450 as suggested by the appearance of a spectrum analogous to a type I binding spectrum. This low-to-high spin conversion was apparently due to a methoxsalen intermediate (probably, covalently bound to the protein and preventing partial sixth ligation of the iron). We conclude that suicide inactivation of cytochrome P-450 by methoxsalen is related to the covalent binding of a methoxsalen intermediate to the protein moiety of several cytochrome P-450 isoenzymes (including UT-A, PB-B/D, PCN-E as well as ISF-G and/or beta NF-B).« less

The α' subunit of β-conglycinin and the A1-5 subunits of glycinin are not essential for many hypolipidemic actions of dietary soy proteins in rats.

PubMed

Chen, Qixuan; Wood, Carla; Gagnon, Christine; Cober, Elroy R; Frégeau-Reid, Judith A; Gleddie, Stephen; Xiao, Chao Wu

2014-08-01

This study examined the effects of dietary soy protein (SP) lacking different storage protein subunits and isoflavones (ISF) on the abdominal fat, blood lipids, thyroid hormones, and enzymatic activities in rats. Weanling Sprague-Dawley rats (8 males and 8 females/group) were fed diets containing either 20 % casein without or with supplemental isoflavones or alcohol-washed SP isolate or SP concentrates (SPC) prepared from 6 different soy bean lines for 8 weeks. Feeding of diets containing SPC regardless of their subunit compositions significantly lowered relative liver weights, blood total, free, and LDL cholesterol in both genders (P < 0.05) and also reduced serum free fatty acids (FFA) and abdominal fat in females (P < 0.05) compared to the casein or casein + ISF diets. Dietary SPC significantly elevated the plasma free triiodothyronine (T3) in both genders and total T3 in females compared to the casein diet (P < 0.05). The SPC lacking β-conglycinin α' and either the glycinin A1-3 or A1-5 subunits increased total T3 in males and reduced plasma enzymatic activities of creatine kinase and lactate dehydrogenase compared to casein or casein + ISF diet (P < 0.05). Soy isoflavones were mainly responsible for the hypocholesterolemic effects and increased plasma free T3, whereas reduction in FFA, abdominal fat, liver weight and increased plasma total T3 were the effects of the soy proteins. Neither the α' subunit of β-conglycinin nor the A1-5 subunits of glycinin are essential for the hypolipidemic properties of soy proteins.

Bioavailability of insulin detemir and human insulin at the level of peripheral interstitial fluid in humans, assessed by open-flow microperfusion.

PubMed

Bodenlenz, M; Ellmerer, M; Schaupp, L; Jacobsen, L V; Plank, J; Brunner, G A; Wutte, A; Aigner, B; Mautner, S I; Pieber, T R

2015-12-01

To find an explanation for the lower potency of insulin detemir observed in humans compared with unmodified human insulin by investigating insulin detemir and human insulin concentrations directly at the level of peripheral insulin-sensitive tissues in humans in vivo. Euglycaemic-hyperinsulinaemic clamp experiments were performed in healthy volunteers. Human insulin was administered i.v. at 6 pmol/kg/min and insulin detemir at 60 pmol/kg/min, achieving a comparable steady-state pharmacodynamic action. In addition, insulin detemir was doubled to 120 pmol/kg/min. Minimally invasive open-flow microperfusion (OFM) sampling methodology was combined with inulin calibration to quantify human insulin and insulin detemir in the interstitial fluid (ISF) of subcutaneous adipose and skeletal muscle tissue. The human insulin concentration in the ISF was ∼115 pmol/l or ∼30% of the serum concentration, whereas the insulin detemir concentration in the ISF was ∼680 pmol/l or ∼2% of the serum concentration. The molar insulin detemir interstitial concentration was five to six times higher than the human insulin interstitial concentration and metabolic clearance of insulin detemir from serum was substantially reduced compared with human insulin. OFM proved useful for target tissue measurements of human insulin and the analogue insulin detemir. Our tissue data confirm a highly effective retention of insulin detemir in the vascular compartment. The higher insulin detemir relative to human insulin tissue concentrations at comparable pharmacodynamics, however, indicate that the lower potency of insulin detemir in humans is attributable to a reduced effect in peripheral insulin-sensitive tissues and is consistent with the reduced in vitro receptor affinity. © 2015 John Wiley & Sons Ltd.

Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviour

PubMed Central

Dean, Ben; Freeman, Robin; Kirk, Holly; Leonard, Kerry; Phillips, Richard A.; Perrins, Chris M.; Guilford, Tim

2013-01-01

The use of miniature data loggers is rapidly increasing our understanding of the movements and habitat preferences of pelagic seabirds. However, objectively interpreting behavioural information from the large volumes of highly detailed data collected by such devices can be challenging. We combined three biologging technologies—global positioning system (GPS), saltwater immersion and time–depth recorders—to build a detailed picture of the at-sea behaviour of the Manx shearwater (Puffinus puffinus) during the breeding season. We used a hidden Markov model to explore discrete states within the combined GPS and immersion data, and found that behaviour could be organized into three principal activities representing (i) sustained direct flight, (ii) sitting on the sea surface, and (iii) foraging, comprising tortuous flight interspersed with periods of immersion. The additional logger data verified that the foraging activity corresponded well to the occurrence of diving. Applying this approach to a large tracking dataset revealed that birds from two different colonies foraged in local waters that were exclusive, but overlapped in one key area: the Irish Sea Front (ISF). We show that the allocation of time to each activity differed between colonies, with birds breeding furthest from the ISF spending the greatest proportion of time engaged in direct flight and the smallest proportion of time engaged in foraging activity. This type of analysis has considerable potential for application in future biologging studies and in other taxa. PMID:23034356

Nanotribology of charged polymer brushes

NASA Astrophysics Data System (ADS)

Klein, Jacob

Polymers at surfaces, whose modern understanding may be traced back to early work by Sam Edwards1, have become a paradigm for modification of surface properties, both as steric stabilizers and as remarkable boundary lubricants2. Charged polymer brushes are of particular interest, with both technological implications and especially biological relevance where most macromolecules are charged. In the context of biolubrication, relevant in areas from dry eye syndrome to osteoarthritis, charged polymer surface phases and their complexes with other macromolecules may play a central role. The hydration lubrication paradigm, where tenaciously-held yet fluid hydration shells surrounding ions or zwitterions serve as highly-efficient friction-reducing elements, has been invoked to understand the excellent lubrication provided both by ionized3 and by zwitterionic4 brushes. In this talk we describe recent advances in our understanding of the nanotribology of such charged brush systems. We consider interactions between charged end-grafted polymers, and how one may disentangle the steric from the electrostatic surface forces5. We examine the limits of lubrication by ionized brushes, both synthetic and of biological origins, and how highly-hydrated zwitterionic chains may provide extremely effective boundary lubrication6. Finally we describe how the lubrication of articular cartilage in the major joints, a tribosystem presenting some of the greatest challenges and opportunities, may be understood in terms of a supramolecular synergy between charged surface-attached polymers and zwitterionic groups7. Work supported by European Research Council (HydrationLube), Israel Science Foundation (ISF), Petroleum Research Fund of the American Chemical Society, ISF-NSF China Joint Program.

Structural, magnetic properties, and electronic structure of hexagonal FeCoSn compound

NASA Astrophysics Data System (ADS)

Li, Yong; Dai, Xue-Fang; Liu, Guo-Dong; Wei, Zhi-Yang; Liu, En-Ke; Han, Xiao-Lei; Du, Zhi-Wei; Xi, Xue-Kui; Wang, Wen-Hong; Wu, Guang-Heng

2018-02-01

Not Available Project supported by the National Natural Science Foundation of China (Grant Nos. 51431009 and 51271038), the Joint NSFC-ISF Research Program, Jointly Funded by the National Natural Science Foundation of China and the Israel Science Foundation (Grant No. 51561145003).

Novel flaviviruses from mosquitoes: Mosquito-specific evolutionary lineages within the phylogenetic group of mosquito-borne flaviviruses

PubMed Central

Huhtamo, Eili; Cook, Shelley; Moureau, Gregory; Uzcátegui, Nathalie Y.; Sironen, Tarja; Kuivanen, Suvi; Putkuri, Niina; Kurkela, Satu; Harbach, Ralph E.; Firth, Andrew E.; Vapalahti, Olli; Gould, Ernest A.; de Lamballerie, Xavier

2014-01-01

Novel flaviviruses that are genetically related to pathogenic mosquito-borne flaviviruses (MBFV) have been isolated from mosquitoes in various geographical locations, including Finland. We isolated and characterized another novel virus of this group from Finnish mosquitoes collected in 2007, designated as Ilomantsi virus (ILOV). Unlike the MBFV that infect both vertebrates and mosquitoes, the MBFV-related viruses appear to be specific to mosquitoes similar to the insect-specific flaviviruses (ISFs). In this overview of MBFV-related viruses we conclude that they differ from the ISFs genetically and antigenically. Phylogenetic analyses separated the MBFV-related viruses isolated in Africa, the Middle East and South America from those isolated in Europe and Asia. Serological cross-reactions of MBFV-related viruses with other flaviviruses and their potential for vector-borne transmission require further characterization. The divergent MBFV-related viruses are probably significantly under sampled to date and provide new information on the variety, properties and evolution of vector-borne flaviviruses. PMID:25108382

Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

NASA Astrophysics Data System (ADS)

Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

2016-12-01

Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

Superensemble forecasts of dengue outbreaks

PubMed Central

Kandula, Sasikiran; Shaman, Jeffrey

2016-01-01

In recent years, a number of systems capable of predicting future infectious disease incidence have been developed. As more of these systems are operationalized, it is important that the forecasts generated by these different approaches be formally reconciled so that individual forecast error and bias are reduced. Here we present a first example of such multi-system, or superensemble, forecast. We develop three distinct systems for predicting dengue, which are applied retrospectively to forecast outbreak characteristics in San Juan, Puerto Rico. We then use Bayesian averaging methods to combine the predictions from these systems and create superensemble forecasts. We demonstrate that on average, the superensemble approach produces more accurate forecasts than those made from any of the individual forecasting systems. PMID:27733698

50 CFR 660.55 - Allocations.

Code of Federal Regulations, 2012 CFR

2012-10-01

... of fishery allocations, the ACL or ACT when specified is reduced by the Pacific Coast treaty Indian... deducted from the ACL or ACT when specified. (2) The commercial harvest guideline for Pacific whiting is...(f) and 600.745, will be deducted from the ACL or ACT when specified. Set-aside amounts will be...

Assessment of reservoir system variable forecasts

NASA Astrophysics Data System (ADS)

Kistenmacher, Martin; Georgakakos, Aris P.

2015-05-01

Forecast ensembles are a convenient means to model water resources uncertainties and to inform planning and management processes. For multipurpose reservoir systems, forecast types include (i) forecasts of upcoming inflows and (ii) forecasts of system variables and outputs such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. Forecasts of system variables and outputs are conditional on forecasted inflows as well as on specific management policies and can provide useful information for decision-making processes. Unlike inflow forecasts (in ensemble or other forms), which have been the subject of many previous studies, reservoir system variable and output forecasts are not formally assessed in water resources management theory or practice. This article addresses this gap and develops methods to rectify potential reservoir system forecast inconsistencies and improve the quality of management-relevant information provided to stakeholders and managers. The overarching conclusion is that system variable and output forecast consistency is critical for robust reservoir management and needs to be routinely assessed for any management model used to inform planning and management processes. The above are demonstrated through an application from the Sacramento-American-San Joaquin reservoir system in northern California.

A short-term ensemble wind speed forecasting system for wind power applications

NASA Astrophysics Data System (ADS)

Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

2011-12-01

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

A study for systematic errors of the GLA forecast model in tropical regions

NASA Technical Reports Server (NTRS)

Chen, Tsing-Chang; Baker, Wayman E.; Pfaendtner, James; Corrigan, Martin

1988-01-01

From the sensitivity studies performed with the Goddard Laboratory for Atmospheres (GLA) analysis/forecast system, it was revealed that the forecast errors in the tropics affect the ability to forecast midlatitude weather in some cases. Apparently, the forecast errors occurring in the tropics can propagate to midlatitudes. Therefore, the systematic error analysis of the GLA forecast system becomes a necessary step in improving the model's forecast performance. The major effort of this study is to examine the possible impact of the hydrological-cycle forecast error on dynamical fields in the GLA forecast system.

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

NASA Astrophysics Data System (ADS)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

First-principles investigations of iron-based alloys and their properties

NASA Astrophysics Data System (ADS)

Limmer, Krista Renee

Fundamental understanding of the complex interactions governing structure-property relationships in iron-based alloys is necessary to advance ferrous metallurgy. Two key components of alloy design are carbide formation and stabilization and controlling the active deformation mechanism. Following a first-principles methodology, understanding on the electronic level of these components has been gained for predictive modeling of alloys. Transition metal carbides have long played an important role in alloy design, though the complexity of their interactions with the ferrous matrix is not well understood. Bulk, surface, and interface properties of vanadium carbide, VCx, were calculated to provide insight for the carbide formation and stability. Carbon vacancy defects are shown to stabilize the bulk carbide due to increased V-V bonding in addition to localized increased V-C bond strength. The VCx (100) surface energy is minimized when carbon vacancies are at least two layers from the surface. Further, the Fe/VC interface is stabilized through maintaining stoichiometry at the Fe/VC interface. Intrinsic and unstable stacking fault energy, gammaisf and gamma usf respectively, were explicitly calculated in nonmagnetic fcc Fe-X systems for X = Al, Si, P, S, and the 3d and 4d transition elements. A parabolic relationship is observed in gamma isf across the transition metals with minimums observed for Mn and Tc in the 3d and 4d periods, respectively. Mn is the only alloying addition that was shown to decrease gamma isf in fcc Fe at the given concentration. The effect of alloying on gammausf also has a parabolic relationship, with all additions decreasing gammaisf yielding maximums for Fe and Rh.

Pregnancy Outcomes and Insulin Requirements in Women with Type 1 Diabetes Treated with Continuous Subcutaneous Insulin Infusion and Multiple Daily Injections: Cohort Study.

PubMed

Abell, Sally K; Suen, Matthew; Pease, Anthony; Boyle, Jacqueline A; Soldatos, Georgia; Regan, John; Wallace, Euan M; Teede, Helena J

2017-05-01

We aimed to compare glycemic control, insulin requirements, and outcomes in women with type 1 diabetes in pregnancy treated with continuous subcutaneous insulin infusion (CSII) and multiple daily injections (MDI). A retrospective cohort study was conducted of singleton pregnancies (>20 weeks gestation) in women with type 1 diabetes (2010-2015) at a specialist multidisciplinary maternity network in Australia. Antenatal characteristics, diabetes history and treatment details, and maternal and neonatal outcomes were compared for women with type 1 diabetes using CSII and MDI. Bolus calculator settings were reviewed for CSII. Data were obtained from individual medical records, linkage to pathology, and the Birthing Outcomes System database. There were no differences in maternal characteristics or diabetes history between women managed with CSII (n = 40) and MDI (n = 127). Women treated with CSII required less insulin and less increase in total daily insulin dose/kg than MDI (40% vs. 52%). Both groups achieved similar glycemic control and no differences in pregnancy outcome. In the CSII group, carbohydrate:insulin ratios were intensified across gestation (30% breakfast, 27% lunch, 22% dinner), and insulin sensitivity factors (ISFs) changed little (7% breakfast, 0% lunch, -10% dinner). There was no difference in glycemic control or pregnancy outcomes in women using CSII or MDI managed in a multidisciplinary setting. Greater adjustments are needed to ISFs with CSII therapy. Overall, these data do not support recommending CSII in pregnancy with potentially higher patient and staff demands and costs and lack of improvement in HbA1c and pregnancy outcomes.

National Centers for Environmental Prediction

Science.gov Websites

SYSTEM CFS CLIMATE FORECAST SYSTEM NAQFC NAQFC MODEL GEFS GLOBAL ENSEMBLE FORECAST SYSTEM HWRF HURRICANE WEATHER RESEARCH and FORECASTING HMON HMON - OPERATIONAL HURRICANE FORECASTING WAVEWATCH III WAVEWATCH III

Marketing Sports Facilities: Perspectives from Botswana

ERIC Educational Resources Information Center

Bohutsana, Basuti; Akpata, Dele

2013-01-01

The provision of sports facilities contributes immensely to the growth of sports and leisure activities in the countries where they are provided. In some countries, as was the case in Botswana, the government had to spend millions of dollars to provide new Integrated Sports Facilities (ISF's) as a panacea for the continued poor performance of its…

Novel flaviviruses from mosquitoes: mosquito-specific evolutionary lineages within the phylogenetic group of mosquito-borne flaviviruses.

PubMed

Huhtamo, Eili; Cook, Shelley; Moureau, Gregory; Uzcátegui, Nathalie Y; Sironen, Tarja; Kuivanen, Suvi; Putkuri, Niina; Kurkela, Satu; Harbach, Ralph E; Firth, Andrew E; Vapalahti, Olli; Gould, Ernest A; de Lamballerie, Xavier

2014-09-01

Novel flaviviruses that are genetically related to pathogenic mosquito-borne flaviviruses (MBFV) have been isolated from mosquitoes in various geographical locations, including Finland. We isolated and characterized another novel virus of this group from Finnish mosquitoes collected in 2007, designated as Ilomantsi virus (ILOV). Unlike the MBFV that infect both vertebrates and mosquitoes, the MBFV-related viruses appear to be specific to mosquitoes similar to the insect-specific flaviviruses (ISFs). In this overview of MBFV-related viruses we conclude that they differ from the ISFs genetically and antigenically. Phylogenetic analyses separated the MBFV-related viruses isolated in Africa, the Middle East and South America from those isolated in Europe and Asia. Serological cross-reactions of MBFV-related viruses with other flaviviruses and their potential for vector-borne transmission require further characterization. The divergent MBFV-related viruses are probably significantly under sampled to date and provide new information on the variety, properties and evolution of vector-borne flaviviruses. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Targeting Beta-Amyloid at the CSF: A New Therapeutic Strategy in Alzheimer's Disease.

PubMed

Menendez-Gonzalez, Manuel; Padilla-Zambrano, Huber S; Alvarez, Gabriel; Capetillo-Zarate, Estibaliz; Tomas-Zapico, Cristina; Costa, Agustin

2018-01-01

Although immunotherapies against the amyloid-β (Aβ) peptide tried so date failed to prove sufficient clinical benefit, Aβ still remains the main target in Alzheimer's disease (AD). This article aims to show the rationale of a new therapeutic strategy: clearing Aβ from the CSF continuously (the "CSF-sink" therapeutic strategy). First, we describe the physiologic mechanisms of Aβ clearance and the resulting AD pathology when these mechanisms are altered. Then, we review the experiences with peripheral Aβ-immunotherapy and discuss the related hypothesis of the mechanism of action of "peripheral sink." We also present Aβ-immunotherapies acting on the CNS directly. Finally, we introduce alternative methods of removing Aβ including the "CSF-sink" therapeutic strategy. As soluble peptides are in constant equilibrium between the ISF and the CSF, altering the levels of Aβ oligomers in the CSF would also alter the levels of such proteins in the brain parenchyma. We conclude that interventions based in a "CSF-sink" of Aβ will probably produce a steady clearance of Aβ in the ISF and therefore it may represent a new therapeutic strategy in AD.

The evolutionary origin of the need to sleep: an inevitable consequence of synaptic neurotransmission?

PubMed

Cantor, Robert S

2015-01-01

It is proposed that the evolutionary origin of the need to sleep is the removal of neurotransmitters (NTs) that escape reuptake and accumulate in brain interstitial fluid (ISF). Recent work suggests that the activity of ionotropic postsynaptic receptors, rapidly initiated by binding of NTs to extracellular sites, is modulated over longer times by adsorption of these NTs to the lipid bilayers in which the receptors are embedded. This bilayer-mediated mechanism is far less molecularly specific than binding, so bilayer adsorption of NTs that have diffused into synapses for other receptors would modulate their activity as well. Although NTs are recycled by membrane protein reuptake, the process is less than 100% efficient; a fraction escapes the region in which these specific reuptake proteins are localized and eventually diffuses throughout the ISF. It is estimated that even if only 0.1% of NTs escape reuptake, they would accumulate and adsorb to bilayers in synapses of other receptors sufficiently to affect receptor activity, the harmful consequences of which are avoided by sleep: a period of efficient convective clearance of solutes together with greatly reduced synaptic activity.

Analysis of insulin pump settings in children and adolescents with type 1 diabetes mellitus.

PubMed

Lau, Yu Ning; Korula, Sophy; Chan, Albert K; Heels, Kristine; Krass, Ines; Ambler, Geoffrey

2016-08-01

To characterize current insulin pump settings used in young patients with type 1 diabetes mellitus (T1DM) and to assess their relationship to glycemic control. This retrospective study included patients aged <18 yr old with T1DM >1 yr using a Medtronic pump device. Pump data including number of blood glucose (BG) tests per day, basal and bolus insulin parameters, carbohydrate ratio (CR), and insulin sensitivity factors (ISFs) were averaged over 14 d for statistical analyses. Anthropometric data and recent glycosylated hemoglobin A1c (HbA1c) were recorded. A total of 292 patients (144 males and 148 females) were included in the study. Participants had a median age (interquartile range, IQR) of 12.9 yr (10.0-15.1 yr) and pump duration of 2.8 yr (1.5-4.2 yr). No significant differences in median HbA1c (IQR) were observed in preschool [n = 14; HbA1c 7.8% (7.3-8.3%)], prepubertal [n = 105; HbA1c 8.1% (7.7-8.9%)], and adolescent subjects [n = 173; HbA1c 8.4% (7.7-9.0%)]. Adolescents took significantly fewer boluses and BG tests per day compared with younger children (p < 0.05). Age-specific diurnal variation in basal insulin delivery was noted. Additionally, stronger carbohydrate cover and weaker corrections were used in real-life compared with theoretical 500 and 100 rules, respectively. Lower HbA1c was associated with higher number of daily boluses, greater number of BG tests per day, lower average CR/500 rule ratio, and higher average ISF/100 rule ratio adjusted for age (R(2) = 0.22; p < 0.01). Insulin pump therapy requires continuous adjustments and glycemic targets are achieved by a minority. We believe this is the first study in pediatric cohort looking at association between CR and ISF with glycemic control. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A seasonal hydrologic ensemble prediction system for water resource management

NASA Astrophysics Data System (ADS)

Luo, L.; Wood, E. F.

2006-12-01

A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.

A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

NASA Astrophysics Data System (ADS)

Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

2017-04-01

Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.

A Prototype Regional GSI-based EnKF-Variational Hybrid Data Assimilation System for the Rapid Refresh Forecasting System: Dual-Resolution Implementation and Testing Results

NASA Astrophysics Data System (ADS)

Pan, Yujie; Xue, Ming; Zhu, Kefeng; Wang, Mingjun

2018-05-01

A dual-resolution (DR) version of a regional ensemble Kalman filter (EnKF)-3D ensemble variational (3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution (HR) deterministic background forecast with lower-resolution (LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/˜13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation (GSI) 3D variational (3DVar) analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar. Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.

Analyzing Effect of System Inertia on Grid Frequency Forecasting Usnig Two Stage Neuro-Fuzzy System

NASA Astrophysics Data System (ADS)

Chourey, Divyansh R.; Gupta, Himanshu; Kumar, Amit; Kumar, Jitesh; Kumar, Anand; Mishra, Anup

2018-04-01

Frequency forecasting is an important aspect of power system operation. The system frequency varies with load-generation imbalance. Frequency variation depends upon various parameters including system inertia. System inertia determines the rate of fall of frequency after the disturbance in the grid. Though, inertia of the system is not considered while forecasting the frequency of power system during planning and operation. This leads to significant errors in forecasting. In this paper, the effect of inertia on frequency forecasting is analysed for a particular grid system. In this paper, a parameter equivalent to system inertia is introduced. This parameter is used to forecast the frequency of a typical power grid for any instant of time. The system gives appreciable result with reduced error.

Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts

NASA Astrophysics Data System (ADS)

Christensen, Hannah; Moroz, Irene; Palmer, Tim

2015-04-01

Forecast verification is important across scientific disciplines as it provides a framework for evaluating the performance of a forecasting system. In the atmospheric sciences, probabilistic skill scores are often used for verification as they provide a way of unambiguously ranking the performance of different probabilistic forecasts. In order to be useful, a skill score must be proper -- it must encourage honesty in the forecaster, and reward forecasts which are reliable and which have good resolution. A new score, the Error-spread Score (ES), is proposed which is particularly suitable for evaluation of ensemble forecasts. It is formulated with respect to the moments of the forecast. The ES is confirmed to be a proper score, and is therefore sensitive to both resolution and reliability. The ES is tested on forecasts made using the Lorenz '96 system, and found to be useful for summarising the skill of the forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) is evaluated using the ES. Its performance is compared to a perfect statistical probabilistic forecast -- the ECMWF high resolution deterministic forecast dressed with the observed error distribution. This generates a forecast that is perfectly reliable if considered over all time, but which does not vary from day to day with the predictability of the atmospheric flow. The ES distinguishes between the dynamically reliable EPS forecasts and the statically reliable dressed deterministic forecasts. Other skill scores are tested and found to be comparatively insensitive to this desirable forecast quality. The ES is used to evaluate seasonal range ensemble forecasts made with the ECMWF System 4. The ensemble forecasts are found to be skilful when compared with climatological or persistence forecasts, though this skill is dependent on region and time of year.

Interactive Forecasting with the National Weather Service River Forecast System

NASA Technical Reports Server (NTRS)

Smith, George F.; Page, Donna

1993-01-01

The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

Teaching Sustainability in the Anthropocene

NASA Astrophysics Data System (ADS)

Ibarra, D. L.

2017-12-01

Human impact on our planet Earth and its ecosystems is well documented and a new epoch, Anthropocene, has been suggested within the scientific community. As educators in the 21st century we are tasked within our communities to teach both the impacts of mankind on our planet and help students to design solutions that will solve a multitude of life threatening challenges. At ISF Academy in Hong Kong, faculty are working collaboratively within the whole school community to educate students about the fundamental problems facing society today and give students to skills to creatively solve these problems locally, regionally, and globally. As a leading school in HK, the physical campus has been updated to provide students with hands-on opportunities to see the latest technologies used for sustainable development. Recently added infrastructure includes air pollution monitoring equipment, an energy management system, aerobic food waste composting, organic garden, bio-diverse landscaping, and photovoltaic renewable energy. The design of each of these systems allows for students to interact directly with the equipment, and conduct student-led research. The curriculum across the campus is designed for all students K-12 and there is an on-going effort to make cross-disciplinary links. The programs outside of the classroom include ecology trips in the Asia region, experiential learning programs that allow students to learn first hand the climate change challenges for communities in distress, and field trips where students work with local experts. Also within the context of the school, there is a new established maker-space that will allow students to work collaboratively together while testing and prototyping their solutions. Hong Kong will need to solve many pressing problems in the next few years and this will require expertise, new innovations, and behaviour changes on the part of all citizens. Our goal at ISF Academy is to equip our students with the required background knowledge to help solve these problems.

Performance of an Advanced MOS System in the 1996-97 National Collegiate Weather Forecasting Contest.

NASA Astrophysics Data System (ADS)

Vislocky, Robert L.; Fritsch, J. Michael

1997-12-01

A prototype advanced model output statistics (MOS) forecast system that was entered in the 1996-97 National Collegiate Weather Forecast Contest is described and its performance compared to that of widely available objective guidance and to contest participants. The prototype system uses an optimal blend of aviation (AVN) and nested grid model (NGM) MOS forecasts, explicit output from the NGM and Eta guidance, and the latest surface weather observations from the forecast site. The forecasts are totally objective and can be generated quickly on a personal computer. Other "objective" forms of guidance tracked in the contest are 1) the consensus forecast (i.e., the average of the forecasts from all of the human participants), 2) the combination of NGM raw output (for precipitation forecasts) and NGM MOS guidance (for temperature forecasts), and 3) the combination of Eta Model raw output (for precipitation forecasts) and AVN MOS guidance (for temperature forecasts).Results show that the advanced MOS system finished in 20th place out of 737 original entrants, or better than approximately 97% of the human forecasters who entered the contest. Moreover, the advanced MOS system was slightly better than consensus (23d place). The fact that an objective forecast system finished ahead of consensus is a significant accomplishment since consensus is traditionally a very formidable "opponent" in forecast competitions. Equally significant is that the advanced MOS system was superior to the traditional guidance products available from the National Centers for Environmental Prediction (NCEP). Specifically, the combination of NGM raw output and NGM MOS guidance finished in 175th place, and the combination of Eta Model raw output and AVN MOS guidance finished in 266th place. The latter result is most intriguing since the proposed elimination of all NGM products would likely result in a serious degradation of objective products disseminated by NCEP, unless they are replaced with equal or better substitutes. On the other hand, the positive performance of the prototype advanced MOS system shows that it is possible to create a single objective product that is not only superior to currently available objective guidance products, but is also on par with some of the better human forecasters.

The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

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

Finley, Cathy

2014-04-30

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

2017-04-01

Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.

Drought Monitoring and Forecasting Using the Princeton/U Washington National Hydrologic Forecasting System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Roundy, J. K.; Lettenmaier, D. P.; Mo, K. C.; Xia, Y.; Ek, M. B.

2011-12-01

Extreme hydrologic events in the form of droughts or floods are a significant source of social and economic damage in many parts of the world. Having sufficient warning of extreme events allows managers to prepare for and reduce the severity of their impacts. A hydrologic forecast system can give seasonal predictions that can be used by mangers to make better decisions; however there is still much uncertainty associated with such a system. Therefore it is important to understand the forecast skill of the system before transitioning to operational usage. Seasonal reforecasts (1982 - 2010) from the NCEP Climate Forecast System (both version 1 (CFS) and version 2 (CFSv2), Climate Prediction Center (CPC) outlooks and the European Seasonal Interannual Prediction (EUROSIP) system, are assessed for forecasting skill in drought prediction across the U.S., both singularly and as a multi-model system The Princeton/U Washington national hydrologic monitoring and forecast system is being implemented at NCEP/EMC via their Climate Test Bed as the experimental hydrological forecast system to support U.S. operational drought prediction. Using our system, the seasonal forecasts are biased corrected, downscaled and used to drive the Variable Infiltration Capacity (VIC) land surface model to give seasonal forecasts of hydrologic variables with lead times of up to six months. Results are presented for a number of events, with particular focus on the Apalachicola-Chattahoochee-Flint (ACF) River Basin in the South Eastern United States, which has experienced a number of severe droughts in recent years and is a pilot study basin for the National Integrated Drought Information System (NIDIS). The performance of the VIC land surface model is evaluated using observational forcing when compared to observed streamflow. The effectiveness of the forecast system to predict streamflow and soil moisture is evaluated when compared with observed streamflow and modeled soil moisture driven by observed atmospheric forcing. The forecast skills from the dynamical seasonal models (CFSv1, CFSv2, EUROSIP) and CPC are also compared with forecasts based on the Ensemble Streamflow Prediction (ESP) method, which uses initial conditions and historical forcings to generate seasonal forecasts. The skill of the system to predict drought, drought recovery and related hydrological conditions such as low-flows is assessed, along with quantified uncertainty.

Short Term Load Forecasting with Fuzzy Logic Systems for power system planning and reliability-A Review

NASA Astrophysics Data System (ADS)

Holmukhe, R. M.; Dhumale, Mrs. Sunita; Chaudhari, Mr. P. S.; Kulkarni, Mr. P. P.

2010-10-01

Load forecasting is very essential to the operation of Electricity companies. It enhances the energy efficient and reliable operation of power system. Forecasting of load demand data forms an important component in planning generation schedules in a power system. The purpose of this paper is to identify issues and better method for load foecasting. In this paper we focus on fuzzy logic system based short term load forecasting. It serves as overview of the state of the art in the intelligent techniques employed for load forecasting in power system planning and reliability. Literature review has been conducted and fuzzy logic method has been summarized to highlight advantages and disadvantages of this technique. The proposed technique for implementing fuzzy logic based forecasting is by Identification of the specific day and by using maximum and minimum temperature for that day and finally listing the maximum temperature and peak load for that day. The results show that Load forecasting where there are considerable changes in temperature parameter is better dealt with Fuzzy Logic system method as compared to other short term forecasting techniques.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

Evaluating glymphatic pathway function utilizing clinically relevant intrathecal infusion of CSF tracer.

PubMed

Yang, Lijun; Kress, Benjamin T; Weber, Harris J; Thiyagarajan, Meenakshisundaram; Wang, Baozhi; Deane, Rashid; Benveniste, Helene; Iliff, Jeffrey J; Nedergaard, Maiken

2013-05-01

Neurodegenerative diseases such as Alzheimer's are associated with the aggregation of endogenous peptides and proteins that contribute to neuronal dysfunction and loss. The glymphatic system, a brain-wide perivascular pathway along which cerebrospinal fluid (CSF) and interstitial fluid (ISF) rapidly exchange, has recently been identified as a key contributor to the clearance of interstitial solutes from the brain, including amyloid β. These findings suggest that measuring changes in glymphatic pathway function may be an important prognostic for evaluating neurodegenerative disease susceptibility or progression. However, no clinically acceptable approach to evaluate glymphatic pathway function in humans has yet been developed. Time-sequenced ex vivo fluorescence imaging of coronal rat and mouse brain slices was performed at 30-180 min following intrathecal infusion of CSF tracer (Texas Red- dextran-3, MW 3 kD; FITC- dextran-500, MW 500 kD) into the cisterna magna or lumbar spine. Tracer influx into different brain regions (cortex, white matter, subcortical structures, and hippocampus) in rat was quantified to map the movement of CSF tracer following infusion along both routes, and to determine whether glymphatic pathway function could be evaluated after lumbar intrathecal infusion. Following lumbar intrathecal infusions, small molecular weight TR-d3 entered the brain along perivascular pathways and exchanged broadly with the brain ISF, consistent with the initial characterization of the glymphatic pathway in mice. Large molecular weight FITC-d500 remained confined to the perivascular spaces. Lumbar intrathecal infusions exhibited a reduced and delayed peak parenchymal fluorescence intensity compared to intracisternal infusions. Lumbar intrathecal contrast delivery is a clinically useful approach that could be used in conjunction with dynamic contrast enhanced MRI nuclear imaging to assess glymphatic pathway function in humans.

Evaluating glymphatic pathway function utilizing clinically relevant intrathecal infusion of CSF tracer

PubMed Central

2013-01-01

Background Neurodegenerative diseases such as Alzheimer’s are associated with the aggregation of endogenous peptides and proteins that contribute to neuronal dysfunction and loss. The glymphatic system, a brain-wide perivascular pathway along which cerebrospinal fluid (CSF) and interstitial fluid (ISF) rapidly exchange, has recently been identified as a key contributor to the clearance of interstitial solutes from the brain, including amyloid β. These findings suggest that measuring changes in glymphatic pathway function may be an important prognostic for evaluating neurodegenerative disease susceptibility or progression. However, no clinically acceptable approach to evaluate glymphatic pathway function in humans has yet been developed. Methods Time-sequenced ex vivo fluorescence imaging of coronal rat and mouse brain slices was performed at 30–180 min following intrathecal infusion of CSF tracer (Texas Red- dextran-3, MW 3 kD; FITC- dextran-500, MW 500 kD) into the cisterna magna or lumbar spine. Tracer influx into different brain regions (cortex, white matter, subcortical structures, and hippocampus) in rat was quantified to map the movement of CSF tracer following infusion along both routes, and to determine whether glymphatic pathway function could be evaluated after lumbar intrathecal infusion. Results Following lumbar intrathecal infusions, small molecular weight TR-d3 entered the brain along perivascular pathways and exchanged broadly with the brain ISF, consistent with the initial characterization of the glymphatic pathway in mice. Large molecular weight FITC-d500 remained confined to the perivascular spaces. Lumbar intrathecal infusions exhibited a reduced and delayed peak parenchymal fluorescence intensity compared to intracisternal infusions. Conclusion Lumbar intrathecal contrast delivery is a clinically useful approach that could be used in conjunction with dynamic contrast enhanced MRI nuclear imaging to assess glymphatic pathway function in humans. PMID:23635358

Distribution of enrofloxacin and its active metabolite, using an in vivo ultrafiltration sampling technique after the injection of enrofloxacin to pigs.

PubMed

Messenger, K M; Papich, M G; Blikslager, A T

2012-10-01

The objective of this study was to determine the pharmacokinetics (PK) of enrofloxacin in pigs and compare to the tissue interstitial fluid (ISF). Six healthy, young pigs were administered 7.5 mg/kg enrofloxacin subcutaneously (SC). Blood and ISF samples were collected from preplaced intravenous catheters and ultrafiltration sampling probes placed in three different tissue sites (intramuscular, subcutaneous, and intrapleural). Enrofloxacin concentrations were measured using high-pressure liquid chromatography with fluorescence detection, PK parameters were analyzed using a one-compartment model, and protein binding was determined using a microcentrifugation system. Concentrations of the active metabolite ciprofloxacin were negligible. The mean ± SD enrofloxacin plasma half-life, volume of distribution, clearance, and peak concentration were 26.6 ± 6.2 h (harmonic mean), 6.4 ± 1.2 L/kg, 0.18 ± 0.08 L/kg/h, and 1.1 ± 0.3 μg/mL, respectively. The half-life of enrofloxacin from the tissues was 23.6 h, and the maximum concentration was 1.26 μg/mL. Tissue penetration, as measured by a ratio of area-under-the-curve (AUC), was 139% (± 69%). Plasma protein binding was 31.1% and 37.13% for high and low concentrations, respectively. This study demonstrated that the concentration of biologically active enrofloxacin in tissues exceeds the concentration predicted by the unbound fraction of enrofloxacin in pig plasma. At a dose of 7.5 mg/kg SC, the high tissue concentrations and long half-life produce an AUC/MIC ratio sufficient for the pathogens that cause respiratory infections in pigs. © 2011 Blackwell Publishing Ltd.

Recent Trends in Variable Generation Forecasting and Its Value to the Power System

DOE PAGES

Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; ...

2014-12-23

We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

NASA Astrophysics Data System (ADS)

Spirig, Christoph; Bhend, Jonas; Liniger, Mark

2016-04-01

Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

NASA Astrophysics Data System (ADS)

Radziukynas, V.; Klementavičius, A.

2016-04-01

The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011) and planned wind power capacities (the year 2023).

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara; ...

2017-06-16

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Building the Sun4Cast System: Improvements in Solar Power Forecasting

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

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Resolution of Probabilistic Weather Forecasts with Application in Disease Management.

PubMed

Hughes, G; McRoberts, N; Burnett, F J

2017-02-01

Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.

The Texas Children's Hospital immunization forecaster: conceptualization to implementation.

PubMed

Cunningham, Rachel M; Sahni, Leila C; Kerr, G Brady; King, Laura L; Bunker, Nathan A; Boom, Julie A

2014-12-01

Immunization forecasting systems evaluate patient vaccination histories and recommend the dates and vaccines that should be administered. We described the conceptualization, development, implementation, and distribution of a novel immunization forecaster, the Texas Children's Hospital (TCH) Forecaster. In 2007, TCH convened an internal expert team that included a pediatrician, immunization nurse, software engineer, and immunization subject matter experts to develop the TCH Forecaster. Our team developed the design of the model, wrote the software, populated the Excel tables, integrated the software, and tested the Forecaster. We created a table of rules that contained each vaccine's recommendations, minimum ages and intervals, and contraindications, which served as the basis for the TCH Forecaster. We created 15 vaccine tables that incorporated 79 unique dose states and 84 vaccine types to operationalize the entire United States recommended immunization schedule. The TCH Forecaster was implemented throughout the TCH system, the Indian Health Service, and the Virginia Department of Health. The TCH Forecast Tester is currently being used nationally. Immunization forecasting systems might positively affect adherence to vaccine recommendations. Efforts to support health care provider utilization of immunization forecasting systems and to evaluate their impact on patient care are needed.

Probabilistic empirical prediction of seasonal climate: evaluation and potential applications

NASA Astrophysics Data System (ADS)

Dieppois, B.; Eden, J.; van Oldenborgh, G. J.

2017-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a new evaluation of an established empirical system used to predict seasonal climate across the globe. Forecasts for surface air temperature, precipitation and sea level pressure are produced by the KNMI Probabilistic Empirical Prediction (K-PREP) system every month and disseminated via the KNMI Climate Explorer (climexp.knmi.nl). K-PREP is based on multiple linear regression and built on physical principles to the fullest extent with predictive information taken from the global CO2-equivalent concentration, large-scale modes of variability in the climate system and regional-scale information. K-PREP seasonal forecasts for the period 1981-2016 will be compared with corresponding dynamically generated forecasts produced by operational forecast systems. While there are many regions of the world where empirical forecast skill is extremely limited, several areas are identified where K-PREP offers comparable skill to dynamical systems. We discuss two key points in the future development and application of the K-PREP system: (a) the potential for K-PREP to provide a more useful basis for reference forecasts than those based on persistence or climatology, and (b) the added value of including K-PREP forecast information in multi-model forecast products, at least for known regions of good skill. We also discuss the potential development of stakeholder-driven applications of the K-PREP system, including empirical forecasts for circumboreal fire activity.

Hybrid Intrusion Forecasting Framework for Early Warning System

NASA Astrophysics Data System (ADS)

Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

Farmers' Perception of Integrated Soil Fertility and Nutrient Management for Sustainable Crop Production: A Study of Rural Areas in Bangladesh

ERIC Educational Resources Information Center

Farouque, Md. Golam; Takeya, Hiroyuki

2007-01-01

This study aimed to determine farmers' perception of integrated soil fertility and nutrient management for sustainable crop production. Integrated soil fertility (ISF) and nutrient management (NM) is an advanced approach to maintain soil fertility and to enhance crop productivity. A total number of 120 farmers from eight villages in four districts…

Evaluation and Analysis of Solid Waste at ISF Academy

NASA Astrophysics Data System (ADS)

Ma, D. W. J.

2017-12-01

Waste management is one of the biggest environmental problems in Hong Kong. According to a report from the HK government, in less than 3 years, which is 2020, all the local landfills will be filled with trash. Therefore, ISF Academy, a school in HK with 1800 students, is planning to reduce their solid waste on campus by evaluating and analysing all solid wastes, which can assist professionals to reform and innovate solutions for refuse disposal. Meanwhile, this project is designed for both raising students' awareness of the magnitude of waste and figuring out measures for waste reduction. For one thing, the project includes the promotion of Waste Audit to reach the former purpose by teaching students how to sort waste. In addition, the weight of each type of waste will be recorded as reference data for students to learn about varied degrees of quantities among different kinds of garbage and relate data to impacts brought by waste with diverse characteristics on the environment. For another, the researcher involved in this project will carry out solutions corresponding to various sorts of waste by applying scientific knowledge, carrying out surveys, organizing campaigns etc.

Self-powered microneedle-based biosensors for pain-free high-accuracy measurement of glycaemia in interstitial fluid.

PubMed

Strambini, L M; Longo, A; Scarano, S; Prescimone, T; Palchetti, I; Minunni, M; Giannessi, D; Barillaro, G

2015-04-15

In this work a novel self-powered microneedle-based transdermal biosensor for pain-free high-accuracy real-time measurement of glycaemia in interstitial fluid (ISF) is reported. The proposed transdermal biosensor makes use of an array of silicon-dioxide hollow microneedles that are about one order of magnitude both smaller (borehole down to 4µm) and more densely-packed (up to 1×10(6)needles/cm(2)) than state-of-the-art microneedles used for biosensing so far. This allows self-powered (i.e. pump-free) uptake of ISF to be carried out with high efficacy and reliability in a few seconds (uptake rate up to 1µl/s) by exploiting capillarity in the microneedles. By coupling the microneedles operating under capillary-action with an enzymatic glucose biosensor integrated on the back-side of the needle-chip, glucose measurements are performed with high accuracy (±20% of the actual glucose level for 96% of measures) and reproducibility (coefficient of variation 8.56%) in real-time (30s) over the range 0-630mg/dl, thus significantly improving microneedle-based biosensor performance with respect to the state-of-the-art. Copyright © 2014 Elsevier B.V. All rights reserved.

The NRL relocatable ocean/acoustic ensemble forecast system

NASA Astrophysics Data System (ADS)

Rowley, C.; Martin, P.; Cummings, J.; Jacobs, G.; Coelho, E.; Bishop, C.; Hong, X.; Peggion, G.; Fabre, J.

2009-04-01

A globally relocatable regional ocean nowcast/forecast system has been developed to support rapid implementation of new regional forecast domains. The system is in operational use at the Naval Oceanographic Office for a growing number of regional and coastal implementations. The new system is the basis for an ocean acoustic ensemble forecast and adaptive sampling capability. We present an overview of the forecast system and the ocean ensemble and adaptive sampling methods. The forecast system consists of core ocean data analysis and forecast modules, software for domain configuration, surface and boundary condition forcing processing, and job control, and global databases for ocean climatology, bathymetry, tides, and river locations and transports. The analysis component is the Navy Coupled Ocean Data Assimilation (NCODA) system, a 3D multivariate optimum interpolation system that produces simultaneous analyses of temperature, salinity, geopotential, and vector velocity using remotely-sensed SST, SSH, and sea ice concentration, plus in situ observations of temperature, salinity, and currents from ships, buoys, XBTs, CTDs, profiling floats, and autonomous gliders. The forecast component is the Navy Coastal Ocean Model (NCOM). The system supports one-way nesting and multiple assimilation methods. The ensemble system uses the ensemble transform technique with error variance estimates from the NCODA analysis to represent initial condition error. Perturbed surface forcing or an atmospheric ensemble is used to represent errors in surface forcing. The ensemble transform Kalman filter is used to assess the impact of adaptive observations on future analysis and forecast uncertainty for both ocean and acoustic properties.

Value of long-term streamflow forecast to reservoir operations for water supply in snow-dominated catchments

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

Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea F.

In this study, we develop a forecast-based adaptive control framework for Oroville reservoir, California, to assess the value of seasonal and inter-annual forecasts for reservoir operation.We use an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity hydrology model. The optimal sequence of daily release decisions from the reservoir is then determined by Model Predictive Control, a flexible and adaptive optimization scheme.We assess the forecast value by comparing system performance based on the ESP forecasts with that based on climatology and a perfect forecast. In addition, we evaluate system performance based onmore » a synthetic forecast, which is designed to isolate the contribution of seasonal and inter-annual forecast skill to the overall value of the ESP forecasts.Using the same ESP forecasts, we generalize our results by evaluating forecast value as a function of forecast skill, reservoir features, and demand. Our results show that perfect forecasts are valuable when the water demand is high and the reservoir is sufficiently large to allow for annual carry-over. Conversely, ESP forecast value is highest when the reservoir can shift water on a seasonal basis.On average, for the system evaluated here, the overall ESP value is 35% less than the perfect forecast value. The inter-annual component of the ESP forecast contributes 20-60% of the total forecast value. Improvements in the seasonal component of the ESP forecast would increase the overall ESP forecast value between 15 and 20%.« less

Wind Power Forecasting Error Distributions: An International Comparison; Preprint

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

Hodge, B. M.; Lew, D.; Milligan, M.

2012-09-01

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Real-time emergency forecasting technique for situation management systems

NASA Astrophysics Data System (ADS)

Kopytov, V. V.; Kharechkin, P. V.; Naumenko, V. V.; Tretyak, R. S.; Tebueva, F. B.

2018-05-01

The article describes the real-time emergency forecasting technique that allows increasing accuracy and reliability of forecasting results of any emergency computational model applied for decision making in situation management systems. Computational models are improved by the Improved Brown’s method applying fractal dimension to forecast short time series data being received from sensors and control systems. Reliability of emergency forecasting results is ensured by the invalid sensed data filtering according to the methods of correlation analysis.

Louisiana Airport System Plan aviation activity forecasts 1990-2010.

DOT National Transportation Integrated Search

1991-07-01

This report documents the methodology used to develop the aviation activity forecasts prepared as a part of the update to the Louisiana Airport System Plan and provides Louisiana aviation forecasts for the years 1990 to 2010. In general, the forecast...

Real-time forecasting at weekly timescales of the SST and SLA of the Ligurian Sea with a satellite-based ocean forecasting (SOFT) system

NASA Astrophysics Data System (ADS)

ÁLvarez, A.; Orfila, A.; Tintoré, J.

2004-03-01

Satellites are the only systems able to provide continuous information on the spatiotemporal variability of vast areas of the ocean. Relatively long-term time series of satellite data are nowadays available. These spatiotemporal time series of satellite observations can be employed to build empirical models, called satellite-based ocean forecasting (SOFT) systems, to forecast certain aspects of future ocean states. SOFT systems can predict satellite-observed fields at different timescales. The forecast skill of SOFT systems forecasting the sea surface temperature (SST) at monthly timescales has been extensively explored in previous works. In this work we study the performance of two SOFT systems forecasting, respectively, the SST and sea level anomaly (SLA) at weekly timescales, that is, providing forecasts of the weekly averaged SST and SLA fields with 1 week in advance. The SOFT systems were implemented in the Ligurian Sea (Western Mediterranean Sea). Predictions from the SOFT systems are compared with observations and with the predictions obtained from persistence models. Results indicate that the SOFT system forecasting the SST field is always superior in terms of predictability to persistence. Minimum prediction errors in the SST are obtained during winter and spring seasons. On the other hand, the biggest differences between the performance of SOFT and persistence models are found during summer and autumn. These changes in the predictability are explained on the basis of the particular variability of the SST field in the Ligurian Sea. Concerning the SLA field, no improvements with respect to persistence have been found for the SOFT system forecasting the SLA field.

Great Lakes Maps - NOAA's National Weather Service

Science.gov Websites

Coastal Forecast System) Waves (GLERL Great Lakes Coastal Forecast System) Ice Cover (GLERL Great Lakes Coastal Forecast System) NOAA's National Weather Service Central Region Headquarters Regional Office 7220

Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

NASA Astrophysics Data System (ADS)

Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

2014-03-01

To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

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

Tian, Tian; Chernyakhovskiy, Ilya; Brancucci Martinez-Anido, Carlo

This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

Assessing the viability of `over-the-loop' real-time short-to-medium range ensemble streamflow forecasts

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Mendoza, P. A.; Nijssen, B.; Newman, A. J.; Clark, M. P.; Arnold, J.; Nowak, K. C.

2016-12-01

Many if not most national operational short-to-medium range streamflow prediction systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow are automated, but others require the hands-on-effort of an experienced human forecaster. This approach evolved out of the need to correct for deficiencies in the models and datasets that were available for forecasting, and often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess and incorporate process variations, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast ensembles and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun to develop more centralized, `over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, the operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as the systems are being rolled out in major operational forecasting centers. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis, Research, and Prediction' (SHARP) to implement, assess and demonstrate real-time over-the-loop forecasts. We present early hindcast and verification results from SHARP for short to medium range streamflow forecasts in a number of US case study watersheds.

First Assessment of Itaipu Dam Ensemble Inflow Forecasting System

NASA Astrophysics Data System (ADS)

Mainardi Fan, Fernando; Machado Vieira Lisboa, Auder; Gomes Villa Trinidad, Giovanni; Rógenes Monteiro Pontes, Paulo; Collischonn, Walter; Tucci, Carlos; Costa Buarque, Diogo

2017-04-01

Inflow forecasting for Hydropower Plants (HPP) Dams is one of the prominent uses for hydrological forecasts. A very important HPP in terms of energy generation for South America is the Itaipu Dam, located in the Paraná River, between Brazil and Paraguay countries, with a drainage area of 820.000km2. In this work, we present the development of an ensemble forecasting system for Itaipu, operational since November 2015. The system is based in the MGB-IPH hydrological model, includes hydrodynamics simulations of the main river, and is run every day morning forced by seven different rainfall forecasts: (i) CPTEC-ETA 15km; (ii) CPTEC-BRAMS 5km; (iii) SIMEPAR WRF Ferrier; (iv) SIMEPAR WRF Lin; (v) SIMEPAR WRF Morrison; (vi) SIMEPAR WRF WDM6; (vii) SIMEPAR MEDIAN. The last one (vii) corresponds to the median value of SIMEPAR WRF model versions (iii to vi) rainfall forecasts. Besides the developed system, the "traditional" method for inflow forecasting generation for the Itaipu Dam is also run every day. This traditional method consists in the approximation of the future inflow based on the discharge tendency of upstream telemetric gauges. Nowadays, after all the forecasts are run, the hydrology team of Itaipu develop a consensus forecast, based on all obtained results, which is the one used for the Itaipu HPP Dam operation. After one year of operation a first evaluation of the Ensemble Forecasting System was conducted. Results show that the system performs satisfactory for rising flows up to five days lead time. However, some false alarms were also issued by most ensemble members in some cases. And not in all cases the system performed better than the traditional method, especially during hydrograph recessions. In terms of meteorological forecasts, some members usage are being discontinued. In terms of the hydrodynamics representation, it seems that a better information of rivers cross section could improve hydrographs recession curves forecasts. Those opportunities for improvements are currently being addressed in the system next update.

Design of a Forecasting Service System for Monitoring of Vulnerabilities of Sensor Networks

NASA Astrophysics Data System (ADS)

Song, Jae-Gu; Kim, Jong Hyun; Seo, Dong Il; Kim, Seoksoo

This study aims to reduce security vulnerabilities of sensor networks which transmit data in an open environment by developing a forecasting service system. The system is to remove or monitor causes of breach incidents in advance. To that end, this research first examines general security vulnerabilities of sensor networks and analyzes characteristics of existing forecasting systems. Then, 5 steps of a forecasting service system are proposed in order to improve security responses.

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.; Galelli, Stefano

2017-09-01

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made - namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

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

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strongmore » relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.« less

Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

DOE PAGES

Turner, Sean W. D.; Bennett, James C.; Robertson, David E.; ...

2017-09-28

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strongmore » relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.« less

Progress and challenges with Warn-on-Forecast

NASA Astrophysics Data System (ADS)

Stensrud, David J.; Wicker, Louis J.; Xue, Ming; Dawson, Daniel T.; Yussouf, Nusrat; Wheatley, Dustan M.; Thompson, Therese E.; Snook, Nathan A.; Smith, Travis M.; Schenkman, Alexander D.; Potvin, Corey K.; Mansell, Edward R.; Lei, Ting; Kuhlman, Kristin M.; Jung, Youngsun; Jones, Thomas A.; Gao, Jidong; Coniglio, Michael C.; Brooks, Harold E.; Brewster, Keith A.

2013-04-01

The current status and challenges associated with two aspects of Warn-on-Forecast-a National Oceanic and Atmospheric Administration research project exploring the use of a convective-scale ensemble analysis and forecast system to support hazardous weather warning operations-are outlined. These two project aspects are the production of a rapidly-updating assimilation system to incorporate data from multiple radars into a single analysis, and the ability of short-range ensemble forecasts of hazardous convective weather events to provide guidance that could be used to extend warning lead times for tornadoes, hailstorms, damaging windstorms and flash floods. Results indicate that a three-dimensional variational assimilation system, that blends observations from multiple radars into a single analysis, shows utility when evaluated by forecasters in the Hazardous Weather Testbed and may help increase confidence in a warning decision. The ability of short-range convective-scale ensemble forecasts to provide guidance that could be used in warning operations is explored for five events: two tornadic supercell thunderstorms, a macroburst, a damaging windstorm and a flash flood. Results show that the ensemble forecasts of the three individual severe thunderstorm events are very good, while the forecasts from the damaging windstorm and flash flood events, associated with mesoscale convective systems, are mixed. Important interactions between mesoscale and convective-scale features occur for the mesoscale convective system events that strongly influence the quality of the convective-scale forecasts. The development of a successful Warn-on-Forecast system will take many years and require the collaborative efforts of researchers and operational forecasters to succeed.

Challenges for operational forecasting and early warning of rainfall induced landslides

NASA Astrophysics Data System (ADS)

Guzzetti, Fausto

2017-04-01

In many areas of the world, landslides occur every year, claiming lives and producing severe economic and environmental damage. Many of the landslides with human or economic consequences are the result of intense or prolonged rainfall. For this reason, in many areas the timely forecast of rainfall-induced landslides is of both scientific interest and social relevance. In the recent years, there has been a mounting interest and an increasing demand for operational landslide forecasting, and for associated landslide early warning systems. Despite the relevance of the problem, and the increasing interest and demand, only a few systems have been designed, and are currently operated. Inspection of the - limited - literature on operational landslide forecasting, and on the associated early warning systems, reveals that common criteria and standards for the design, the implementation, the operation, and the evaluation of the performances of the systems, are lacking. This limits the possibility to compare and to evaluate the systems critically, to identify their inherent strengths and weaknesses, and to improve the performance of the systems. Lack of common criteria and of established standards can also limit the credibility of the systems, and consequently their usefulness and potential practical impact. Landslides are very diversified phenomena, and the information and the modelling tools used to attempt landslide forecasting vary largely, depending on the type and size of the landslides, the extent of the geographical area considered, the timeframe of the forecasts, and the scope of the predictions. Consequently, systems for landslide forecasting and early warning can be designed and implemented at several different geographical scales, from the local (site or slope specific) to the regional, or even national scale. The talk focuses on regional to national scale landslide forecasting systems, and specifically on operational systems based on empirical rainfall threshold models. Building on the experience gained in designing, implementing, and operating national and regional landslide forecasting systems in Italy, and on a preliminary review of the existing literature on regional landslide early warning systems, the talk discusses concepts, limitations and challenges inherent to the design of reliable forecasting and early warning systems for rainfall-triggered landslides, the evaluation of the performances of the systems, and on problems related to the use of the forecasts and the issuing of landslide warnings. Several of the typical elements of an operational landslide forecasting system are considered, including: (i) the rainfall and landslide information used to establish the threshold models, (ii) the methods and tools used to define the empirical rainfall thresholds, and their associated uncertainty, (iii) the quality (e.g., the temporal and spatial resolution) of the rainfall information used for operational forecasting, including rain gauge and radar measurements, satellite estimates, and quantitative weather forecasts, (iv) the ancillary information used to prepare the forecasts, including e.g., the terrain subdivisions and the landslide susceptibility zonations, (v) the criteria used to transform the forecasts into landslide warnings and the methods used to communicate the warnings, and (vi) the criteria and strategies adopted to evaluate the performances of the systems, and to define minimum or optimal performance levels.

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

NASA Astrophysics Data System (ADS)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.

Validation and Inter-comparison Against Observations of GODAE Ocean View Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xu, J.; Davidson, F. J. M.; Smith, G. C.; Lu, Y.; Hernandez, F.; Regnier, C.; Drevillon, M.; Ryan, A.; Martin, M.; Spindler, T. D.; Brassington, G. B.; Oke, P. R.

2016-02-01

For weather forecasts, validation of forecast performance is done at the end user level as well as by the meteorological forecast centers. In the development of Ocean Prediction Capacity, the same level of care for ocean forecast performance and validation is needed. Herein we present results from a validation against observations of 6 Global Ocean Forecast Systems under the GODAE OceanView International Collaboration Network. These systems include the Global Ocean Ice Forecast System (GIOPS) developed by the Government of Canada, two systems PSY3 and PSY4 from the French Mercator-Ocean Ocean Forecasting Group, the FOAM system from UK met office, HYCOM-RTOFS from NOAA/NCEP/NWA of USA, and the Australian Bluelink-OceanMAPS system from the CSIRO, the Australian Meteorological Bureau and the Australian Navy.The observation data used in the comparison are sea surface temperature, sub-surface temperature, sub-surface salinity, sea level anomaly, and sea ice total concentration data. Results of the inter-comparison demonstrate forecast performance limits, strengths and weaknesses of each of the six systems. This work establishes validation protocols and routines by which all new prediction systems developed under the CONCEPTS Collaborative Network will be benchmarked prior to approval for operations. This includes anticipated delivery of CONCEPTS regional prediction systems over the next two years including a pan Canadian 1/12th degree resolution ice ocean prediction system and limited area 1/36th degree resolution prediction systems. The validation approach of comparing forecasts to observations at the time and location of the observation is called Class 4 metrics. It has been adopted by major international ocean prediction centers, and will be recommended to JCOMM-WMO as routine validation approach for operational oceanography worldwide.

Consensus Seasonal Flood Forecasts and Warning Response System (FFWRS): an alternate for nonstructural flood management in Bangladesh.

PubMed

Chowdhury, Rashed

2005-06-01

Despite advances in short-range flood forecasting and information dissemination systems in Bangladesh, the present system is less than satisfactory. This is because of short lead-time products, outdated dissemination networks, and lack of direct feedback from the end-user. One viable solution is to produce long-lead seasonal forecasts--the demand for which is significantly increasing in Bangladesh--and disseminate these products through the appropriate channels. As observed in other regions, the success of seasonal forecasts, in contrast to short-term forecast, depends on consensus among the participating institutions. The Flood Forecasting and Warning Response System (henceforth, FFWRS) has been found to be an important component in a comprehensive and participatory approach to seasonal flood management. A general consensus in producing seasonal forecasts can thus be achieved by enhancing the existing FFWRS. Therefore, the primary objective of this paper is to revisit and modify the framework of an ideal warning response system for issuance of consensus seasonal flood forecasts in Bangladesh. The five-stage FFWRS-i) Flood forecasting, ii) Forecast interpretation and message formulation, iii) Warning preparation and dissemination, iv) Responses, and v) Review and analysis-has been modified. To apply the concept of consensus forecast, a framework similar to that of the Southern African Regional Climate Outlook Forum (SARCOF) has been discussed. Finally, the need for a climate Outlook Fora has been emphasized for a comprehensive and participatory approach to seasonal flood hazard management in Bangladesh.

A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

NASA Astrophysics Data System (ADS)

Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

2017-12-01

The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

NASA Astrophysics Data System (ADS)

Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications' (SHARP) to implement, assess and demonstrate real-time over-the-loop ensemble flow forecasts in a range of US watersheds. The system relies on fully ensemble techniques, including: an 100-member ensemble of meteorological model forcings and an ensemble particle filter data assimilation for initializing watershed states; analog/regression-based downscaling of ensemble weather forecasts from GEFS; and statistical post-processing of ensemble forecast outputs, all of which run in real-time within a workflow managed by ECWMF's ecFlow libraries over large US regional domains. We describe SHARP and present early hindcast and verification results for short to seasonal range streamflow forecasts in a number of US case study watersheds.

Forecasting, Forecasting

Treesearch

Michael A. Fosberg

1987-01-01

Future improvements in the meteorological forecasts used in fire management will come from improvements in three areas: observational systems, forecast techniques, and postprocessing of forecasts and better integration of this information into the fire management process.

Skill of a global seasonal ensemble streamflow forecasting system

NASA Astrophysics Data System (ADS)

Candogan Yossef, Naze; Winsemius, Hessel; Weerts, Albrecht; van Beek, Rens; Bierkens, Marc

2013-04-01

Forecasting of water availability and scarcity is a prerequisite for managing the risks and opportunities caused by the inter-annual variability of streamflow. Reliable seasonal streamflow forecasts are necessary to prepare for an appropriate response in disaster relief, management of hydropower reservoirs, water supply, agriculture and navigation. Seasonal hydrological forecasting on a global scale could be valuable especially for developing regions of the world, where effective hydrological forecasting systems are scarce. In this study, we investigate the forecasting skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCR-GLOBWB. FEWS-World has been setup within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The assessment in historical simulation mode used a meteorological forcing based on observations from the Climate Research Unit of the University of East Anglia and the ERA-40 reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF). We assessed the skill of the global hydrological model PCR-GLOBWB in reproducing past discharge extremes in 20 large rivers of the world. This preliminary assessment concluded that the prospects for seasonal forecasting with PCR-GLOBWB or comparable models are positive. However this assessment did not include actual meteorological forecasts. Thus the meteorological forcing errors were not assessed. Yet, in a forecasting setup, the predictive skill of a hydrological forecasting system is affected by errors due to uncertainty from numerical weather prediction models. For the assessment in retroactive forecasting mode, the model is forced with actual ensemble forecasts from the seasonal forecast archives of ECMWF. Skill is assessed at 78 stations on large river basins across the globe, for all the months of the year and for lead times up to 6 months. The forecasted discharges are compared with observed monthly streamflow records using the ensemble verification measures Brier Skill Score (BSS) and Continuous Ranked Probability Score (CRPS). The eventual goal is to transfer FEWS-World to operational forecasting mode, where the system will use operational seasonal forecasts from ECMWF. The results will be disseminated on the internet, and hopefully provide information that is valuable for users in data and model-poor regions of the world.

Risky Business: Development, Communication and Use of Hydroclimatic Forecasts

NASA Astrophysics Data System (ADS)

Lall, U.

2012-12-01

Inter-seasonal and longer hydroclimatic forecasts have been made increasingly in the last two decades following the increase in ENSO activity since the early 1980s and the success in seasonal ENSO forecasting. Yet, the number of examples of systematic use of these forecasts and their incorporation into water systems operation continue to be few. This may be due in part to the limited skill in such forecasts over much of the world, but is also likely due to the limited evolution of methods and opportunities to "safely" use uncertain forecasts. There has been a trend to rely more on "physically based" rather than "physically informed" empirical forecasts, and this may in part explain the limited success in developing usable products in more locations. Given the limited skill, forecasters have tended to "dumb" down their forecasts - either formally or subjectively shrinking the forecasts towards climatology, or reducing them to tercile forecasts that serve to obscure the potential information in the forecast. Consequently, the potential utility of such forecasts for decision making is compromised. Water system operating rules are often designed to be robust in the face of historical climate variability, and consequently are adapted to the potential conditions that a forecast seeks to inform. In such situations, there is understandable reluctance by managers to use the forecasts as presented, except in special cases where an alternate course of action is pragmatically appealing in any case. In this talk, I review opportunities to present targeted forecasts for use with decision systems that directly address climate risk and the risk induced by unbiased yet uncertain forecasts, focusing especially on extreme events and water allocation in a competitive environment. Examples from Brazil and India covering surface and ground water conjunctive use strategies that could potentially be insured and lead to improvements over the traditional system operation and resource allocation are provided.

Securing, Stabilizing, and Rebuilding Iraq: Key Issues for Congressional Oversight

DTIC Science & Technology

2007-01-01

Been Constrained by Security, Management , and Funding Challenges 72 U.S. Military Readiness 79 Enclosure XII: Extended Operations Have Had...Forces Have Resulted in Shortages of Critical Items 92 Improving Acquisition Outcomes 97 Enclosure XV: DOD Needs to Improve Its Capacity to Manage ...International Monetary Fund IRMO Iraq Reconstruction Management Office IRRF Iraqi Relief and Reconstruction Fund ISF Iraqi security forces ISFF

Mission Accomplished Rebuilding the Iraqi and Afghan Armies

DTIC Science & Technology

2016-06-01

ACCOMPLISHED? REBUILDING THE IRAQI AND AFGHAN ARMIES by James F. Beal June 2016 Thesis Advisor : James Russell Second Reader: Daniel Moran THIS...and the withdrawal of combat advisors from Afghanistan in 2014, the Islamic State has gained control of significant territory in Iraq including Mosul...Afghanistan National Army, ANA, ISF, IA, counterinsurgency, COIN, military advisor , legitimacy, nation-building 15. NUMBER OF PAGES 103 16. PRICE

Use of medications by people with chronic fatigue syndrome and healthy persons: a population-based study of fatiguing illness in Georgia.

PubMed

Boneva, Roumiana S; Lin, Jin-Mann S; Maloney, Elizabeth M; Jones, James F; Reeves, William C

2009-07-20

Chronic fatigue syndrome (CFS) is a debilitating condition of unknown etiology and no definitive pharmacotherapy. Patients are usually prescribed symptomatic treatment or self-medicate. We evaluated prescription and non-prescription drug use among persons with CFS in Georgia and compared it to that in non-fatigued Well controls and also to chronically Unwell individuals not fully meeting criteria for CFS. A population-based, case-control study. To identify persons with possible CFS-like illness and controls, we conducted a random-digit dialing telephone screening of 19,807 Georgia residents, followed by a detailed telephone interview of 5,630 to identify subjects with CFS-like illness, other chronically Unwell, and Well subjects. All those with CFS-like illness (n = 469), a random sample of chronically Unwell subjects (n = 505), and Well individuals (n = 641) who were age-, sex-, race-, and geographically matched to those with CFS-like illness were invited for a clinical evaluation and 783 participated (48% overall response rate). Clinical evaluation identified 113 persons with CFS, 264 Unwell subjects with insufficient symptoms for CFS (named ISF), and 124 Well controls; the remaining 280 subjects had exclusionary medical or psychiatric conditions, and 2 subjects could not be classified. Subjects were asked to bring all medications taken in the past 2 weeks to the clinic where a research nurse viewed and recorded the name and the dose of each medication. More than 90% of persons with CFS used at least one drug or supplement within the preceding two weeks. Among users, people with CFS used an average of 5.8 drugs or supplements, compared to 4.1 by ISF and 3.7 by Well controls. Persons with CFS were significantly more likely to use antidepressants, sedatives, muscle relaxants, and anti-acids than either Well controls or the ISF group. In addition, persons with CFS were significantly more likely to use pain-relievers, anti-histamines and cold/sinus medications than were Well controls. Medical care providers of patients with chronic fatigue syndrome should be aware of polypharmacy as a problem in such patients, and the related potential iatrogenic effects and drug interactions.

A global flash flood forecasting system

NASA Astrophysics Data System (ADS)

Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

2016-04-01

The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial resolution appropriate to the NWP system. We then demonstrate how these warning areas could eventually complement existing global systems such as the Global Flood Awareness System (GloFAS), to give warnings of flash floods. This work demonstrates the possibility of creating a global flash flood forecasting system based on forecasts from existing global NWP systems. Future developments, in post-processing for example, will need to address an under-prediction bias, for extreme point rainfall, that is innate to current-generation global models.

Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine

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

Jiang, Huaiguang; Zhang, Yingchen

This paper proposes an approach for distribution system state forecasting, which aims to provide an accurate and high speed state forecasting with an optimal synchrophasor sensor placement (OSSP) based state estimator and an extreme learning machine (ELM) based forecaster. Specifically, considering the sensor installation cost and measurement error, an OSSP algorithm is proposed to reduce the number of synchrophasor sensor and keep the whole distribution system numerically and topologically observable. Then, the weighted least square (WLS) based system state estimator is used to produce the training data for the proposed forecaster. Traditionally, the artificial neural network (ANN) and support vectormore » regression (SVR) are widely used in forecasting due to their nonlinear modeling capabilities. However, the ANN contains heavy computation load and the best parameters for SVR are difficult to obtain. In this paper, the ELM, which overcomes these drawbacks, is used to forecast the future system states with the historical system states. The proposed approach is effective and accurate based on the testing results.« less

A probabilistic drought forecasting framework: A combined dynamical and statistical approach

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

Yan, Hongxiang; Moradkhani, Hamid; Zarekarizi, Mahkameh

In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initialmore » condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.« less

Development, Implementation, and Skill Assessment of the NOAA/NOS Great Lakes Operational Forecast System

DTIC Science & Technology

2011-01-01

USA) 2011 Abstract The NOAA Great Lakes Operational Forecast System ( GLOFS ) uses near-real-time atmospheric observa- tions and numerical weather...Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS... GLOFS ) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC. Distribution Statement A: Approved for Public Release; distribution is unlimited

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC.

The Impact of Implementing a Demand Forecasting System into a Low-Income Country’s Supply Chain

PubMed Central

Mueller, Leslie E.; Haidari, Leila A.; Wateska, Angela R.; Phillips, Roslyn J.; Schmitz, Michelle M.; Connor, Diana L.; Norman, Bryan A.; Brown, Shawn T.; Welling, Joel S.; Lee, Bruce Y.

2016-01-01

OBJECTIVE To evaluate the potential impact and value of applications (e.g., ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country’s vaccine supply chain with different levels of population change to urban areas. MATERIALS AND METHODS Using our software, HERMES, we generated a detailed discrete event simulation model of Niger’s entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. RESULTS Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. DISCUSSION The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. CONCLUSION Demand forecasting systems have the potential to greatly improve vaccine demand fulfillment, and decrease logistics cost/dose when implemented with storage and transportation increases direct vaccines. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements. PMID:27219341

The impact of implementing a demand forecasting system into a low-income country's supply chain.

PubMed

Mueller, Leslie E; Haidari, Leila A; Wateska, Angela R; Phillips, Roslyn J; Schmitz, Michelle M; Connor, Diana L; Norman, Bryan A; Brown, Shawn T; Welling, Joel S; Lee, Bruce Y

2016-07-12

To evaluate the potential impact and value of applications (e.g. adjusting ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country's vaccine supply chain with different levels of population change to urban areas. Using our software, HERMES, we generated a detailed discrete event simulation model of Niger's entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. Demand forecasting systems have the potential to greatly improve vaccine demand fulfilment, and decrease logistics cost/dose when implemented with storage and transportation increases. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental Forecasts of Wildfire Pollution at the Canadian Meteorological Centre

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Beaulieu, Paul-Andre; Chen, Jack; Landry, Hugo; Cousineau, Sophie; Moran, Michael

2016-04-01

Environment and Climate Change Canada's Canadian Meteorological Centre Operations division (CMCO) has been running an experimental North American air quality forecast system with near-real-time wildfire emissions since 2014. This system, named FireWork, also takes anthropogenic and other natural emission sources into account. FireWork 48-hour forecasts are provided to CMCO forecasters and external partners in Canada and the U.S. twice daily during the wildfire season. This system has proven to be very useful in capturing short- and long-range smoke transport from wildfires over North America. Several upgrades to the FireWork system have been made since 2014 to accommodate the needs of operational AQ forecasters and to improve system performance. In this talk we will present performance statistics and some case studies for the 2014 and 2015 wildfire seasons. We will also describe current limitations of the FireWork system and ongoing and future work planned for this air quality forecast system.

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

Zhang, Jie; Cui, Mingjian; Hodge, Bri-Mathias

The large variability and uncertainty in wind power generation present a concern to power system operators, especially given the increasing amounts of wind power being integrated into the electric power system. Large ramps, one of the biggest concerns, can significantly influence system economics and reliability. The Wind Forecast Improvement Project (WFIP) was to improve the accuracy of forecasts and to evaluate the economic benefits of these improvements to grid operators. This paper evaluates the ramp forecasting accuracy gained by improving the performance of short-term wind power forecasting. This study focuses on the WFIP southern study region, which encompasses most ofmore » the Electric Reliability Council of Texas (ERCOT) territory, to compare the experimental WFIP forecasts to the existing short-term wind power forecasts (used at ERCOT) at multiple spatial and temporal scales. The study employs four significant wind power ramping definitions according to the power change magnitude, direction, and duration. The optimized swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental WFIP forecasts improve the accuracy of the wind power ramp forecasting. This improvement can result in substantial costs savings and power system reliability enhancements.« less

Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Garzon, Juan L.; Ferreira, Celso M.; Padilla-Hernandez, Roberto

2018-01-01

Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.

Seasonal Forecasting of Reservoir Inflow for the Segura River Basin, Spain

NASA Astrophysics Data System (ADS)

de Tomas, Alberto; Hunink, Johannes

2017-04-01

A major threat to the agricultural sector in Europe is an increasing occurrence of low water availability for irrigation, affecting the local and regional food security and economies. Especially in the Mediterranean region, such as in the Segura river basin (Spain), drought epidodes are relatively frequent. Part of the irrigation water demand in this basin is met by a water transfer from the Tagus basin (central Spain), but also in this basin an increasing pressure on the water resources has reduced the water available to be transferred. Currently, Drought Management Plans in these Spanish basins are in place and mitigate the impact of drought periods to some extent. Drought indicators that are derived from the available water in the storage reservoirs impose a set of drought mitigation measures. Decisions on water transfers are dependent on a regression-based time series forecast from the reservoir inflows of the preceding months. This user-forecast has its limitations and can potentially be improved using more advanced techniques. Nowadays, seasonal climate forecasts have shown to have increasing skill for certain areas and for certain applications. So far, such forecasts have not been evaluated in a seasonal hydrologic forecasting system in the Spanish context. The objective of this work is to develop a prototype of a Seasonal Hydrologic Forecasting System and compare this with a reference forecast. The reference forecast in this case is the locally used regression-based forecast. Additionally, hydrological simulations derived from climatological reanalysis (ERA-Interim) are taken as a reference forecast. The Spatial Processes in Hydrology model (SPHY - http://www.sphy.nl/) forced with the ECMWF- SFS4 (15 ensembles) Seasonal Forecast Systems is used to predict reservoir inflows of the upper basins of the Segura and Tagus rivers. The system is evaluated for 4 seasons with a forecasting lead time of 3 months. First results show that only for certain initialization months and lead times, the developed system outperforms the reference forecast. This research is carried out within the European research project IMPREX (www.imprex.eu) that aims at investigating the value of improving predictions of hydro-meteorological extremes in a number of water sectors, including agriculture . The next step is to integrate improved seasonal forecasts into the system and evaluate these. This should finally lead to a more robust forecasting system that allows water managers and irrigators to better anticipate to drought episodes and putting into practice more effective water allocation and mitigation practices.

The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps

NASA Astrophysics Data System (ADS)

Liechti, K.; Panziera, L.; Germann, U.; Zappa, M.

2013-10-01

This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel radar-based ensemble forecasting chains for flash-flood early warning are investigated in three catchments in the southern Swiss Alps and set in relation to deterministic discharge forecasts for the same catchments. The first radar-based ensemble forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second ensemble forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialised with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. A clear preference was found for the ensemble approach. Discharge forecasts perform better when forced by NORA and REAL-C2 rather then by deterministic weather radar data. Moreover, it was observed that using an ensemble of initial conditions at the forecast initialisation, as in REAL-C2, significantly improved the forecast skill. These forecasts also perform better then forecasts forced by ensemble rainfall forecasts (NORA) initialised form a single initial condition of the hydrological model. Thus the best results were obtained with the REAL-C2 forecasting chain. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

Centralized Storm Information System (CSIS)

NASA Technical Reports Server (NTRS)

Norton, C. C.

1985-01-01

A final progress report is presented on the Centralized Storm Information System (CSIS). The primary purpose of the CSIS is to demonstrate and evaluate real time interactive computerized data collection, interpretation and display techniques as applied to severe weather forecasting. CSIS objectives pertaining to improved severe storm forecasting and warning systems are outlined. The positive impact that CSIS has had on the National Severe Storms Forecast Center (NSSFC) is discussed. The benefits of interactive processing systems on the forecasting ability of the NSSFC are described.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests that for the Blue Nile basin, (1) the combination of GEOS-5 and CFSv2 is equivalent in skill to the full North American Multimodel Ensemble (NMME); and (2) the seasonal water deficit forecasting system skill for both soil moisture and streamflow anomalies is greater than the standard Ensemble Streamflow Prediction (ESP) approach.

Potential for malaria seasonal forecasting in Africa

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Di Giuseppe, Francesca; Colon-Gonzalez, Felipe; Namanya, Didas; Friday, Agabe

2014-05-01

As monthly and seasonal dynamical prediction systems have improved their skill in the tropics over recent years, there is now the potential to use these forecasts to drive dynamical malaria modelling systems to provide early warnings in epidemic and meso-endemic regions. We outline a new pilot operational system that has been developed at ECMWF and ICTP. It uses a precipitation bias correction methodology to seamlessly join the monthly ensemble prediction system (EPS) and seasonal (system 4) forecast systems of ECMWF together. The resulting temperature and rainfall forecasts for Africa are then used to drive the recently developed ICTP malaria model known as VECTRI. The resulting coupled system of ECMWF climate forecasts and VECTRI thus produces predictions of malaria prevalence rates and transmission intensity across Africa. The forecasts are filtered to highlight the regions and months in which the system has particular value due to high year to year variability. In addition to epidemic areas, these also include meso and hyper-endemic regions which undergo considerable variability in the onset months. We demonstrate the limits of the forecast skill as a function of lead-time, showing that for many areas the dynamical system can add one to two months additional warning time to a system based on environmental monitoring. We then evaluate the past forecasts against district level case data in Uganda and show that when interventions can be discounted, the system can show significant skill at predicting interannual variability in transmission intensity up to 3 or 4 months ahead at the district scale. The prospects for a operational implementation will be briefly discussed.

The value of information as applied to the Landsat Follow-on benefit-cost analysis

NASA Technical Reports Server (NTRS)

Wood, D. B.

1978-01-01

An econometric model was run to compare the current forecasting system with a hypothetical (Landsat Follow-on) space-based system. The baseline current system was a hybrid of USDA SRS domestic forecasts and the best known foreign data. The space-based system improved upon the present Landsat by the higher spatial resolution capability of the thematic mapper. This satellite system is a major improvement for foreign forecasts but no better than SRS for domestic forecasts. The benefit analysis was concentrated on the use of Landsat Follow-on to forecast world wheat production. Results showed that it was possible to quantify the value of satellite information and that there are significant benefits in more timely and accurate crop condition information.

An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

2013-12-01

One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.

Development and validation of a regional coupled forecasting system for S2S forecasts

NASA Astrophysics Data System (ADS)

Sun, R.; Subramanian, A. C.; Hoteit, I.; Miller, A. J.; Ralph, M.; Cornuelle, B. D.

2017-12-01

Accurate and efficient forecasting of oceanic and atmospheric circulation is essential for a wide variety of high-impact societal needs, including: weather extremes; environmental protection and coastal management; management of fisheries, marine conservation; water resources; and renewable energy. Effective forecasting relies on high model fidelity and accurate initialization of the models with observed state of the ocean-atmosphere-land coupled system. A regional coupled ocean-atmosphere model with the Weather Research and Forecasting (WRF) model and the MITGCM ocean model coupled using the ESMF (Earth System Modeling Framework) coupling framework is developed to resolve mesoscale air-sea feedbacks. The regional coupled model allows oceanic mixed layer heat and momentum to interact with the atmospheric boundary layer dynamics at the mesoscale and submesoscale spatiotemporal regimes, thus leading to feedbacks which are otherwise not resolved in coarse resolution global coupled forecasting systems or regional uncoupled forecasting systems. The model is tested in two scenarios in the mesoscale eddy rich Red Sea and Western Indian Ocean region as well as mesoscale eddies and fronts of the California Current System. Recent studies show evidence for air-sea interactions involving the oceanic mesoscale in these two regions which can enhance predictability on sub seasonal timescale. We will present results from this newly developed regional coupled ocean-atmosphere model for forecasts over the Red Sea region as well as the California Current region. The forecasts will be validated against insitu observations in the region as well as reanalysis fields.

Forecasting Influenza Epidemics in Hong Kong.

PubMed

Yang, Wan; Cowling, Benjamin J; Lau, Eric H Y; Shaman, Jeffrey

2015-07-01

Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions.

Forecasting Influenza Epidemics in Hong Kong

PubMed Central

Yang, Wan; Cowling, Benjamin J.; Lau, Eric H. Y.; Shaman, Jeffrey

2015-01-01

Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions. PMID:26226185

Self-Organizing Maps-based ocean currents forecasting system.

PubMed

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-03-16

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Self-Organizing Maps-based ocean currents forecasting system

PubMed Central

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-01-01

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training. PMID:26979129

Action-based flood forecasting for triggering humanitarian action

NASA Astrophysics Data System (ADS)

Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

2016-09-01

Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China

NASA Astrophysics Data System (ADS)

Ma, Feng; Ye, Aizhong; Duan, Qingyun

2017-03-01

An experimental seasonal drought forecasting system is developed based on 29-year (1982-2010) seasonal meteorological hindcasts generated by the climate models from the North American Multi-Model Ensemble (NMME) project. This system made use of a bias correction and spatial downscaling method, and a distributed time-variant gain model (DTVGM) hydrologic model. DTVGM was calibrated using observed daily hydrological data and its streamflow simulations achieved Nash-Sutcliffe efficiency values of 0.727 and 0.724 during calibration (1978-1995) and validation (1996-2005) periods, respectively, at the Danjiangkou reservoir station. The experimental seasonal drought forecasting system (known as NMME-DTVGM) is used to generate seasonal drought forecasts. The forecasts were evaluated against the reference forecasts (i.e., persistence forecast and climatological forecast). The NMME-DTVGM drought forecasts have higher detectability and accuracy and lower false alarm rate than the reference forecasts at different lead times (from 1 to 4 months) during the cold-dry season. No apparent advantage is shown in drought predictions during spring and summer seasons because of a long memory of the initial conditions in spring and a lower predictive skill for precipitation in summer. Overall, the NMME-based seasonal drought forecasting system has meaningful skill in predicting drought several months in advance, which can provide critical information for drought preparedness and response planning as well as the sustainable practice of water resource conservation over the basin.

Visualization of ocean forecast in BYTHOS

NASA Astrophysics Data System (ADS)

Zhuk, E.; Zodiatis, G.; Nikolaidis, A.; Stylianou, S.; Karaolia, A.

2016-08-01

The Cyprus Oceanography Center has been constantly searching for new ideas for developing and implementing innovative methods and new developments concerning the use of Information Systems in Oceanography, to suit both the Center's monitoring and forecasting products. Within the frame of this scope two major online managing and visualizing data systems have been developed and utilized, those of CYCOFOS and BYTHOS. The Cyprus Coastal Ocean Forecasting and Observing System - CYCOFOS provides a variety of operational predictions such as ultra high, high and medium resolution ocean forecasts in the Levantine Basin, offshore and coastal sea state forecasts in the Mediterranean and Black Sea, tide forecasting in the Mediterranean, ocean remote sensing in the Eastern Mediterranean and coastal and offshore monitoring. As a rich internet application, BYTHOS enables scientists to search, visualize and download oceanographic data online and in real time. The recent improving of BYTHOS system is the extension with access and visualization of CYCOFOS data and overlay forecast fields and observing data. The CYCOFOS data are stored at OPENDAP Server in netCDF format. To search, process and visualize it the php and python scripts were developed. Data visualization is achieved through Mapserver. The BYTHOS forecast access interface allows to search necessary forecasting field by recognizing type, parameter, region, level and time. Also it provides opportunity to overlay different forecast and observing data that can be used for complex analyze of sea basin aspects.

Cast Iron Inoculation Enhanced by Supplementary Oxy-sulfides Forming Elements

NASA Astrophysics Data System (ADS)

Riposan, Iulian; Stan, Stelian; Uta, Valentin; Stefan, Ion

2017-09-01

Inoculation is one of the most important metallurgical treatments applied to the molten cast iron immediately prior to casting, to promote solidification without excessive eutectic undercooling, which favors carbides formation usually with undesirable graphite morphologies. The paper focused on the separate addition of an inoculant enhancer alloy [S, O, oxy-sulfides forming elements] with a conventional Ca-FeSi alloy, in the production of gray and ductile cast irons. Carbides formation tendency decreased with improved graphite characteristics as an effect of the [Ca-FeSi + Enhancer] inoculation combination, when compared to other Ca/Ca, Ba/Ca, RE-FeSi alloy treatments. Adding an inoculant enhancer greatly enhances inoculation, lowers inoculant consumption up to 50% or more and avoids the need to use more costly inoculants, such as a rare earth bearing alloy. The Inoculation Specific Factor [ISF] was developed as a means to more realistically measure inoculant treatment efficiency. It compares the ratio between the improved characteristic level and total inoculant consumption for this effect. Addition of any of the commercial inoculants plus the inoculant enhancer offered outstanding inoculation power [increased ISF] even at higher solidification cooling rates, even though the total enhancer addition was at a small fraction of the amount of commercial inoculant used.

Formability behavior studies on CP-Al sheets processed through the helical tool path of incremental forming process

NASA Astrophysics Data System (ADS)

Markanday, H.; Nagarajan, D.

2018-02-01

Incremental sheet forming (ISF) is a novel die-less sheet metal forming process, which can produce components directly from the CAD geometry using a CNC milling machine at less production time and cost. The formability of the sheet material used is greatly affected by the process parameters involved and tool path adopted, and the present study is aimed to investigate the influence of different process parameter values using the helical tool path strategy on the formability of a commercial pure Al and to achieve maximum formability in the material. ISF experiments for producing an 80 mm diameter axisymmetric dome were carried out on 2 mm thickness commercially pure Al sheets for different tool speeds and feed rates in a CNC milling machine with a 10 mm hemispherical forming tool. The obtained parts were analyzed for springback, amount of thinning and maximum forming depth. The results showed that when the tool speed was increased by keeping the feed rate constant, the forming depth and thinning were also increased. On contrary, when the feed rate was increased by keeping the tool speed constant, the forming depth and thinning were decreased. Springback was found to be higher when the feed rate was increased rather than the tool speed was increased.

Physical fitness of secondary school adolescents in relation to the body weight and the body composition: classification according to Bioelectrical Impedance Analysis. Part II.

PubMed

Chwałczyńska, Agnieszka; Jędrzejewski, Grzegorz; Lewandowski, Zdzisław; Jonak, Wiesława; Sobiech, Krzysztof A

2017-03-01

Underweight and obesity are important factors affecting the level of physical fitness. The aim of this study was to assess physical fitness of lower secondary school adolescents in relation to BMI. Two-hundred students, aged 14-16, were examined. Respondents were divided into 4 groups according to BMI classification. The body height and weight were determined. Physical fitness was assessed on the basis Zuchora's ISF tests. The body weight deficiency occurred in 3% of girls and 5% of boys, overweight was noted in 14% of both groups, and obesity in 6% and 12% accordingly. Statistically significant differences were determined in the components of physical fitness. They were noted in both genders between the group of children with standard body weight and overweight as well as obese children. Significant negative correlations were determined between and the components of physical fitness. More significant correlations giving evidence to the decrease of Zuchora's ISF score along with the increase of BMI were more significant in girls. Statistically significant differences between the boys and girls were determined in all five Zuchora's tests. The highest scores in physical fitness were achieved by the boys and girls with weight deficiency.

Physical fitness of secondary school adolescents in relation to the body weight and the body composition: classification according to World Health Organization. Part I.

PubMed

Chwałczyńska, Agnieszka; Jędrzejewski, Grzegorz; Socha, Małgorzata; Jonak, Wiesława; Sobiech, Krzysztof A

2017-03-01

Underweight and obesity are important factors affecting the level of physical fitness. The aim of this study was to assess physical fitness of lower secondary school adolescents in relation to BMI. Two-hundred students, aged 14-16, were examined. Respondents were divided into 4 groups according to BMI classification. The body height and weight were determined. Physical fitness was assessed on the basis Zuchora's ISF tests. The body weight deficiency occurred in 3% of girls and 5% of boys, overweight was noted in 14% of both groups, and obesity in 6% and 12% accordingly. Statistically significant differences were determined in the components of physical fitness. They were noted in both genders between the group of children with standard body weight and overweight as well as obese children. Significant negative correlations were determined between and the components of physical fitness. More significant correlations giving evidence to the decrease of Zuchora's ISF score along with the increase of BMI were more significant in girls. Statistically significant differences between the boys and girls were determined in all five Zuchora's tests. The highest scores in physical fitness were achieved by the boys and girls with weight deficiency.

Cell fusing agent virus and dengue virus mutually interact in Aedes aegypti cell lines.

PubMed

Zhang, Guangmei; Asad, Sultan; Khromykh, Alexander A; Asgari, Sassan

2017-07-31

The genus Flavivirus contains more than 70 single-stranded, positive-sense arthropod-borne RNA viruses. Some flaviviruses are particularly medically important to humans and other vertebrates including dengue virus (DENV), West Nile virus, and yellow fever virus. These viruses are transmitted to vertebrates by mosquitoes and other arthropod species. Mosquitoes are also infected by insect-specific flaviviruses (ISFs) that do not appear to be infective to vertebrates. Cell fusing agent virus (CFAV) was the first described ISF, which was discovered in an Aedes aegypti cell culture. We found that while CFAV infection could be significantly reduced by application of RNAi against the NS5 gene, removal of the treatment led to quick restoration of CFAV replication. Interestingly, we found that CFAV infection significantly enhanced replication of DENV, and vice versa, DENV infection significantly enhanced replication of CFAV in mosquito cells. We have shown that CFAV infection leads to increase in the expression of ribonuclease kappa (RNASEK), which is known to promote infection of viruses that rely on endocytosis and pH-dependent entry. Knockdown of RNASEK by dsRNA resulted in reduced DENV replication. Thus, increased expression of RNASEK induced by CFAV is likely to contribute to enhanced DENV replication in CFAV-infected cells.

Mosquito Surveillance for Prevention and Control of Emerging Mosquito-Borne Diseases in Portugal — 2008–2014

PubMed Central

Osório, Hugo C.; Zé-Zé, Líbia; Amaro, Fátima; Alves, Maria J.

2014-01-01

Mosquito surveillance in Europe is essential for early detection of invasive species with public health importance and prevention and control of emerging pathogens. In Portugal, a vector surveillance national program—REVIVE (REde de VIgilância de VEctores)—has been operating since 2008 under the custody of Portuguese Ministry of Health. The REVIVE is responsible for the nationwide surveillance of hematophagous arthropods. Surveillance for West Nile virus (WNV) and other flaviviruses in adult mosquitoes is continuously performed. Adult mosquitoes—collected mainly with Centre for Disease Control light traps baited with CO2—and larvae were systematically collected from a wide range of habitats in 20 subregions (NUTS III). Around 500,000 mosquitoes were trapped in more than 3,000 trap nights and 3,500 positive larvae surveys, in which 24 species were recorded. The viral activity detected in mosquito populations in these years has been limited to insect specific flaviviruses (ISFs) non-pathogenic to humans. Rather than emergency response, REVIVE allows timely detection of changes in abundance and species diversity providing valuable knowledge to health authorities, which may take control measures of vector populations reducing its impact on public health. This work aims to present the REVIVE operation and to expose data regarding mosquito species composition and detected ISFs. PMID:25396768

Development of an Adaptable Display and Diagnostic System for the Evaluation of Tropical Cyclone Forecasts

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Burek, T.; Halley-Gotway, J.

2015-12-01

NCAR's Joint Numerical Testbed Program (JNTP) focuses on the evaluation of experimental forecasts of tropical cyclones (TCs) with the goal of developing new research tools and diagnostic evaluation methods that can be transitioned to operations. Recent activities include the development of new TC forecast verification methods and the development of an adaptable TC display and diagnostic system. The next generation display and diagnostic system is being developed to support evaluation needs of the U.S. National Hurricane Center (NHC) and broader TC research community. The new hurricane display and diagnostic capabilities allow forecasters and research scientists to more deeply examine the performance of operational and experimental models. The system is built upon modern and flexible technology that includes OpenLayers Mapping tools that are platform independent. The forecast track and intensity along with associated observed track information are stored in an efficient MySQL database. The system provides easy-to-use interactive display system, and provides diagnostic tools to examine forecast track stratified by intensity. Consensus forecasts can be computed and displayed interactively. The system is designed to display information for both real-time and for historical TC cyclones. The display configurations are easily adaptable to meet the needs of the end-user preferences. Ongoing enhancements include improving capabilities for stratification and evaluation of historical best tracks, development and implementation of additional methods to stratify and compute consensus hurricane track and intensity forecasts, and improved graphical display tools. The display is also being enhanced to incorporate gridded forecast, satellite, and sea surface temperature fields. The presentation will provide an overview of the display and diagnostic system development and demonstration of the current capabilities.

The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

NASA Astrophysics Data System (ADS)

Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

2010-09-01

Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events, has become evident. However, despite the demonstrated advantages, worldwide the incorporation of HEPS in operational flood forecasting is still limited. The applicability of HEPS for smaller river basins was tested in MAP D-Phase, an acronym for "Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region" which was launched in 2005 as a Forecast Demonstration Project of World Weather Research Programme of WMO, and entered a pre-operational and still active testing phase in 2007. In Europe, a comparatively high number of EPS driven systems for medium-large rivers exist. National flood forecasting centres of Sweden, Finland and the Netherlands, have already implemented HEPS in their operational forecasting chain, while in other countries including France, Germany, Czech Republic and Hungary, hybrids or experimental chains have been installed. As an example of HEPS, the European Flood Alert System (EFAS) is being presented. EFAS provides medium-range probabilistic flood forecasting information for large trans-national river basins. It incorporates multiple sets of weather forecast including different types of EPS and deterministic forecasts from different providers. EFAS products are evaluated and visualised as exceedance of critical levels only - both in forms of maps and time series. Different sources of uncertainty and its impact on the flood forecasting performance for every grid cell has been tested offline but not yet incorporated operationally into the forecasting chain for computational reasons. However, at stations where real-time discharges are available, a hydrological uncertainty processor is being applied to estimate the total predictive uncertainty from the hydrological and input uncertainties. Research on long-term EFAS results has shown the need for complementing statistical analysis with case studies for which examples will be shown.

Traffic flow forecasting for intelligent transportation systems.

DOT National Transportation Integrated Search

1995-01-01

The capability to forecast traffic volume in an operational setting has been identified as a critical need for intelligent transportation systems (ITS). In particular, traffic volume forecasts will directly support proactive traffic control and accur...

Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

NASA Astrophysics Data System (ADS)

Singh, Sanjeev Kumar; Prasad, V. S.

2018-02-01

This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

Assessment of Forecast Sensitivity to Observation and Its Application to Satellite Radiances

NASA Astrophysics Data System (ADS)

Ide, K.

2017-12-01

The Forecast sensitivity to observation provides practical and useful metric for the assessment of observation impact without conducting computationally intensive data denial experiments. Quite often complex data assimilation systems use a simplified version of the forecast sensitivity formulation based on ensembles. In this talk, we first present the comparison of forecast sensitivity for 4DVar, Hybrid-4DEnVar, and 4DEnKF with or without such simplifications using a highly nonlinear model. We then present the results of ensemble forecast sensitivity to satellite radiance observations for Hybrid-4DEnVart using NOAA's Global Forecast System.

The meta-Gaussian Bayesian Processor of forecasts and associated preliminary experiments

NASA Astrophysics Data System (ADS)

Chen, Fajing; Jiao, Meiyan; Chen, Jing

2013-04-01

Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

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

Hoff, Thomas Hoff; Kankiewicz, Adam

Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP)more » forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”« less

How do I know if I’ve improved my continental scale flood early warning system?

NASA Astrophysics Data System (ADS)

Cloke, Hannah L.; Pappenberger, Florian; Smith, Paul J.; Wetterhall, Fredrik

2017-04-01

Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.

NCEP Data Products

Science.gov Websites

Image of NCEP Logo WHERE AMERICA'S CLIMATE AND WEATHER SERVICES BEGIN Inventory of Data Products on Generated Products Image of horizontal rule Global Forecast System (GFS) GFS Ensemble Forecast System (GEFS of horizontal rule External Products Image of horizontal rule Canadian Ensemble Forecast System

Development and Use of the Hydrologic Ensemble Forecast System by the National Weather Service to Support the New York City Water Supply

NASA Astrophysics Data System (ADS)

Shedd, R.; Reed, S. M.; Porter, J. H.

2015-12-01

The National Weather Service (NWS) has been working for several years on the development of the Hydrologic Ensemble Forecast System (HEFS). The objective of HEFS is to provide ensemble river forecasts incorporating the best precipitation and temperature forcings at any specific time horizon. For the current implementation, this includes the Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFSv2). One of the core partners that has been working with the NWS since the beginning of the development phase of HEFS is the New York City Department of Environmental Protection (NYCDEP) which is responsible for the complex water supply system for New York City. The water supply system involves a network of reservoirs in both the Delaware and Hudson River basins. At the same time that the NWS was developing HEFS, NYCDEP was working on enhancing the operations of their water supply reservoirs through the development of a new Operations Support Tool (OST). OST is designed to guide reservoir system operations to ensure an adequate supply of high-quality drinking water for the city, as well as to meet secondary objectives for reaches downstream of the reservoirs assuming the primary water supply goals can be met. These secondary objectives include fisheries and ecosystem support, enhanced peak flow attenuation beyond that provided natively by the reservoirs, salt front management, and water supply for other cities. Since January 2014, the NWS Northeast and Middle Atlantic River Forecast Centers have provided daily one year forecasts from HEFS to NYCDEP. OST ingests these forecasts, couples them with near-real-time environmental and reservoir system data, and drives models of the water supply system. The input of ensemble forecasts results in an ensemble of model output, from which information on the range and likelihood of possible future system states can be extracted. This type of probabilistic information provides system managers with additional information not available from deterministic forecasts and allows managers to better assess risk, and provides greater context for decision-making than has been available in the past. HEFS has allowed NYCDEP water supply managers to make better decisions on reservoir operations than they likely would have in the past, using only deterministic forecasts.

The Copernicus Atmosphere Monitoring Service: facilitating the prediction of air quality from global to local scales

NASA Astrophysics Data System (ADS)

Engelen, R. J.; Peuch, V. H.

2017-12-01

The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The regional forecasts are produced by an ensemble of seven operational European air quality models that take their boundary conditions from the global system and provide an ensemble median with ensemble spread as their main output. Both the global and regional forecasting systems are feeding their output into air quality models on a variety of scales in various parts of the world. We will introduce the CAMS service chain and provide illustrations of its use in downstream applications. Both the usage of the daily forecasts and the usage of global and regional reanalyses will be addressed.

Impact of Lidar Wind Sounding on Mesoscale Forecast

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Chou, Shih-Hung; Goodman, H. Michael (Technical Monitor)

2001-01-01

An Observing System Simulation Experiment (OSSE) was conducted to study the impact of airborne lidar wind sounding on mesoscale weather forecast. A wind retrieval scheme, which interpolates wind data from a grid data system, simulates the retrieval of wind profile from a satellite lidar system. A mesoscale forecast system based on the PSU/NCAR MM5 model is developed and incorporated the assimilation of the retrieved line-of-sight wind. To avoid the "identical twin" problem, the NCEP reanalysis data is used as our reference "nature" atmosphere. The simulated space-based lidar wind observations were retrieved by interpolating the NCEP values to the observation locations. A modified dataset obtained by smoothing the NCEP dataset was used as the initial state whose forecast was sought to be improved by assimilating the retrieved lidar observations. Forecasts using wind profiles with various lidar instrument parameters has been conducted. The results show that to significantly improve the mesoscale forecast the satellite should fly near the storm center with large scanning radius. Increasing lidar firing rate also improves the forecast. Cloud cover and lack of aerosol degrade the quality of the lidar wind data and, subsequently, the forecast.

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

USGS Publications Warehouse

Funk, Chris; Verdin, James P.; Husak, Gregory

2007-01-01

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

An Approach to Assess Observation Impact Based on Observation-Minus-Forecast Residuals

NASA Technical Reports Server (NTRS)

Todling, Ricardo

2009-01-01

Langland and Baker (2004) introduced an approach to assess the impact of observations on the forecasts. In that, a state-space aspect of the forecast is defined and a procedure is derived that relates changes in the aspect with changes in the initial conditions associated with the assimilation of observations) ultimately providing information about the impact of individual observations on the forecast. Some features of the approach are to be noted. The typical choice of forecast aspect employed in related works is rather arbitrary and leads to an incomplete assessment of the observing system. Furthermore, the state-space forecast aspect requires availability of a verification state that should ideally be uncorrelated with the forecast but in practice is not. Lastly, the approach involves the adjoint operator of the entire data assimilation system and as such it is constrained by the validity of this operator. In this presentation, an observation-space metric is used that, for a relatively time-homogeneous observing system, allows inferring observation impact on the forecast without some of the limitations above. Specifically, using observation-minus-forecast residuals leads to an approach with the following features: (i) it suggests a rather natural choice of forecast aspect, directly linked to the analysis system and providing full assessment of the observations; (ii) it naturally avoids introducing undesirable correlations in the forecast aspect by verifying against the observations; and (iii) it does not involve linearization and use of adjoints; therefore being applicable to any length of forecast. The state and observation-space approaches might be complementary to some degree, and involve different limitations and complexities. Illustrations are given using the NASA GEOS-5 data.

Short-term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System

NASA Astrophysics Data System (ADS)

Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin

2015-12-01

In this study the forecast skill of the U.S. Navy operational Arctic sea ice forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period February 2014 to June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic sea ice and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include ice concentration, ice thickness, ice velocity, sea surface temperature, sea surface salinity, and sea surface velocities. Ice concentration forecast skill is compared to a persistent ice state and historical sea ice climatology. Skill scores are focused on areas where ice concentration changes by ±5% or more, and are therefore limited to primarily the marginal ice zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent ice state, especially beyond 24 h. ACNFS is also shown to be particularly skilful compared to a climatologic state for forecasts up to 102 h. Modeled ice drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015, ACNFS began to assimilate a blended ice concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and Ice Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and ice edge location compared to the independently derived National Ice Center Ice Edge product.

The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, M. P.; Nijssen, B.

2017-12-01

Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and weaknesses of each strategy map onto the requirements for different types of forecasting services (e.g., flash flooding, river flooding, seasonal water supply prediction).

Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

2017-11-01

Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias-correction method should be further investigated to remedy this weakness and take more advantage of the ensemble forecasts produced by the climate model. Overall, in this study, bias-corrected ensemble meteorological forecasts appear to be an interesting source of information for hydrological forecasting for lead times up to 1 month. They could also complement ESP for longer lead times.

Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements

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

Optis, Michael; Scott, George N.; Draxl, Caroline

The goal of this analysis was to assess the wind power forecast accuracy of the Vermont Weather Analytics Center (VTWAC) forecast system and to identify potential improvements to the forecasts. Based on the analysis at Georgia Mountain, the following recommendations for improving forecast performance were made: 1. Resolve the significant negative forecast bias in February-March 2017 (50% underprediction on average) 2. Improve the ability of the forecast model to capture the strong diurnal cycle of wind power 3. Add ability for forecast model to assess internal wake loss, particularly at sites where strong diurnal shifts in wind direction are present.more » Data availability and quality limited the robustness of this forecast assessment. A more thorough analysis would be possible given a longer period of record for the data (at least one full year), detailed supervisory control and data acquisition data for each wind plant, and more detailed information on the forecast system input data and methodologies.« less

VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS

EPA Science Inventory

An air quality forecast (AQF) system has been established at NOAA/NCEP since 2003 as a collaborative effort of NOAA and EPA. The system is based on NCEP's Eta mesoscale meteorological model and EPA's CMAQ air quality model (Davidson et al, 2004). The vision behind this system is ...

Operational seasonal forecasting of crop performance.

PubMed

Stone, Roger C; Meinke, Holger

2005-11-29

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.

Operational seasonal forecasting of crop performance

PubMed Central

Stone, Roger C; Meinke, Holger

2005-01-01

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

Satellite based Ocean Forecasting, the SOFT project

NASA Astrophysics Data System (ADS)

Stemmann, L.; Tintoré, J.; Moneris, S.

2003-04-01

The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

Developing Environmental Scanning/Forecasting Systems To Augment Community College Planning.

ERIC Educational Resources Information Center

Morrison, James L.; Held, William G.

A description is provided of a conference session that was conducted to explore the structure and function of an environmental scanning/forecasting system that could be used in a community college to facilitate planning. Introductory comments argue that a college that establishes an environmental scanning and forecasting system is able to identify…

Flash-flood early warning using weather radar data: from nowcasting to forecasting

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Panziera, Luca; Germann, Urs; Zappa, Massimiliano

2013-04-01

In our study we explore the limits of radar-based forecasting for hydrological runoff prediction. Two novel probabilistic radar-based forecasting chains for flash-flood early warning are investigated in three catchments in the Southern Swiss Alps and set in relation to deterministic discharge forecast for the same catchments. The first probabilistic radar-based forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second probabilistic forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialized with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 hours between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. We found a clear preference for the probabilistic approach. Discharge forecasts perform better when forced by NORA rather than by a persistent radar QPE for lead times up to eight hours and for all discharge thresholds analysed. The best results were, however, obtained with the REAL-C2 forecasting chain, which was also remarkably skilful even with the highest thresholds. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic forcing.

Flash-flood early warning using weather radar data: from nowcasting to forecasting

NASA Astrophysics Data System (ADS)

Liechti, K.; Panziera, L.; Germann, U.; Zappa, M.

2013-01-01

This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel probabilistic radar-based forecasting chains for flash-flood early warning are investigated in three catchments in the Southern Swiss Alps and set in relation to deterministic discharge forecast for the same catchments. The first probabilistic radar-based forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second probabilistic forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialized with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. We found a clear preference for the probabilistic approach. Discharge forecasts perform better when forced by NORA rather than by a persistent radar QPE for lead times up to eight hours and for all discharge thresholds analysed. The best results were, however, obtained with the REAL-C2 forecasting chain, which was also remarkably skilful even with the highest thresholds. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

Short-Term State Forecasting-Based Optimal Voltage Regulation in Distribution Systems: Preprint

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

Yang, Rui; Jiang, Huaiguang; Zhang, Yingchen

2017-05-17

A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severemore » voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.« less

The Value of Humans in the Operational River Forecasting Enterprise

NASA Astrophysics Data System (ADS)

Pagano, T. C.

2012-04-01

The extent of human control over operational river forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and realtime data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Automated data quality algorithms, if used at all, are typically very basic (e.g. checks for impossible values); substantial human effort is devoted to cleaning up forcing data using subjective methods. Similarly, although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts, instead relying on the assessment of meteorologists. Conversely, while there is a strong tradition in meteorology of making raw model outputs available to forecast users via the Internet, this is rarely done in hydrology; Operational river forecasters express concerns about exposing users to raw guidance, due to the potential for misinterpretation and misuse. However, this limits the ability of users to build their confidence in operational products through their own value-added analyses. Forecasting agencies also struggle with provenance (i.e. documenting the production process and archiving the pieces that went into creating a forecast) although this is necessary for quantifying the benefits of human involvement in forecasting and diagnosing weak links in the forecasting chain. In hydrology, the space between model outputs and final operational products is nearly unstudied by the academic community, although some studies exist in other fields such as meteorology.

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign

NASA Astrophysics Data System (ADS)

Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.

2015-12-01

The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.

On the reliability of seasonal climate forecasts.

PubMed

Weisheimer, A; Palmer, T N

2014-07-06

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time.

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

Improving medium-range and seasonal hydroclimate forecasts in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, Di

Accurate hydro-climate forecasts are important for decision making by water managers, agricultural producers, and other stake holders. Numerical weather prediction models and general circulation models may have potential for improving hydro-climate forecasts at different scales. In this study, forecast analogs of the Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) based on different approaches were evaluated for medium-range reference evapotranspiration (ETo), irrigation scheduling, and urban water demand forecasts in the southeast United States; the Climate Forecast System version 2 (CFSv2) and the North American national multi-model ensemble (NMME) were statistically downscaled for seasonal forecasts of ETo, precipitation (P) and 2-m temperature (T2M) at the regional level. The GFS mean temperature (Tmean), relative humidity, and wind speed (Wind) reforecasts combined with the climatology of Reanalysis 2 solar radiation (Rs) produced higher skill than using the direct GFS output only. Constructed analogs showed slightly higher skill than natural analogs for deterministic forecasts. Both irrigation scheduling driven by the GEFS-based ETo forecasts and GEFS-based ETo forecast skill were generally positive up to one week throughout the year. The GEFS improved ETo forecast skill compared to the GFS. The GEFS-based analog forecasts for the input variables of an operational urban water demand model were skillful when applied in the Tampa Bay area. The modified operational models driven by GEFS analog forecasts showed higher forecast skill than the operational model based on persistence. The results for CFSv2 seasonal forecasts showed maximum temperature (Tmax) and Rs had the greatest influence on ETo. The downscaled Tmax showed the highest predictability, followed by Tmean, Tmin, Rs, and Wind. The CFSv2 model could better predict ETo in cold seasons during El Nino Southern Oscillation (ENSO) events only when the forecast initial condition was in ENSO. Downscaled P and T2M forecasts were produced by directly downscaling the NMME P and T2M output or indirectly using the NMME forecasts of Nino3.4 sea surface temperatures to predict local-scale P and T2M. The indirect method generally showed the highest forecast skill which occurs in cold seasons. The bias-corrected NMME ensemble forecast skill did not outperform the best single model.

Long-range forecast of all India summer monsoon rainfall using adaptive neuro-fuzzy inference system: skill comparison with CFSv2 model simulation and real-time forecast for the year 2015

NASA Astrophysics Data System (ADS)

Chaudhuri, S.; Das, D.; Goswami, S.; Das, S. K.

2016-11-01

All India summer monsoon rainfall (AISMR) characteristics play a vital role for the policy planning and national economy of the country. In view of the significant impact of monsoon system on regional as well as global climate systems, accurate prediction of summer monsoon rainfall has become a challenge. The objective of this study is to develop an adaptive neuro-fuzzy inference system (ANFIS) for long range forecast of AISMR. The NCEP/NCAR reanalysis data of temperature, zonal and meridional wind at different pressure levels have been taken to construct the input matrix of ANFIS. The membership of the input parameters for AISMR as high, medium or low is estimated with trapezoidal membership function. The fuzzified standardized input parameters and the de-fuzzified target output are trained with artificial neural network models. The forecast of AISMR with ANFIS is compared with non-hybrid multi-layer perceptron model (MLP), radial basis functions network (RBFN) and multiple linear regression (MLR) models. The forecast error analyses of the models reveal that ANFIS provides the best forecast of AISMR with minimum prediction error of 0.076, whereas the errors with MLP, RBFN and MLR models are 0.22, 0.18 and 0.73 respectively. During validation with observations, ANFIS shows its potency over the said comparative models. Performance of the ANFIS model is verified through different statistical skill scores, which also confirms the aptitude of ANFIS in forecasting AISMR. The forecast skill of ANFIS is also observed to be better than Climate Forecast System version 2. The real-time forecast with ANFIS shows possibility of deficit (65-75 cm) AISMR in the year 2015.

Assessing skill of a global bimonthly streamflow ensemble prediction system

NASA Astrophysics Data System (ADS)

van Dijk, A. I.; Peña-Arancibia, J.; Sheffield, J.; Wood, E. F.

2011-12-01

Ideally, a seasonal streamflow forecasting system might be conceived of as a system that ingests skillful climate forecasts from general circulation models and propagates these through thoroughly calibrated hydrological models that are initialised using hydrometric observations. In practice, there are practical problems with each of these aspects. Instead, we analysed whether a comparatively simple hydrological model-based Ensemble Prediction System (EPS) can provide global bimonthly streamflow forecasts with some skill and if so, under what circumstances the greatest skill may be expected. The system tested produces ensemble forecasts for each of six annual bimonthly periods based on the previous 30 years of global daily gridded 1° resolution climate variables and an initialised global hydrological model. To incorporate some of the skill derived from ocean conditions, a post-EPS analog method was used to sample from the ensemble based on El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) index values observed prior to the forecast. Forecasts skill was assessed through a hind-casting experiment for the period 1979-2008. Potential skill was calculated with reference to a model run with the actual forcing for the forecast period (the 'perfect' model) and was compared to actual forecast skill calculated for each of the six forecast times for an average 411 Australian and 51 pan-tropical catchments. Significant potential skill in bimonthly forecasts was largely limited to northern regions during the snow melt period, seasonally wet tropical regions at the transition of wet to dry season, and the Indonesian region where rainfall is well correlated to ENSO. The actual skill was approximately 34-50% of the potential skill. We attribute this primarily to limitations in the model structure, parameterisation and global forcing data. Use of better climate forecasts and remote sensing observations of initial catchment conditions should help to increase actual skill in future. Future work also could address the potential skill gain from using weather and climate forecasts and from a calibrated and/or alternative hydrological model or model ensemble. The approach and data might be useful as a benchmark for joint seasonal forecasting experiments planned under GEWEX.

Measuring Stability and Security in Iraq

DTIC Science & Technology

2008-12-01

majority of the country. On September 1, 2008, Anbar Province, once an AQI stronghold, transferred to Provincial Iraqi Control ( PIC ). With the...transfer of Babil and Wasit Provinces to PIC in October 2008, the ISF is now in charge of security operations in the majority of Iraq’s 18 provinces... PIC ). Security responsibility for Babil Province was handed over to the GoI on October 23, 2008, and Wasit Province transitioned to PIC on October

VizieR Online Data Catalog: Orion Integral Filament ALMA+IRAM30m N2H+(1-0) data (Hacar+, 2018)

NASA Astrophysics Data System (ADS)

Hacar, A.; Tafalla, M.; Forbrich, J.; Alves, J.; Meingast, S.; Grossschedl, J.; Teixeira, P. S.

2018-01-01

Combined ALMA+IRAM30m large-scale N2H+(1-0) emission in the Orion ISF. Two datasets are presented here in FITS format: 1.- Full data cube: spectral resolution = 0.1 kms-1 2.- Total integrated line intensity (moment 0) map Units are in Jy/beam See also: https://sites.google.com/site/orion4dproject/home (2 data files).

A Direct Mechanism of Ultrafast Intramolecular Singlet Fission in Pentacene Dimers

DTIC Science & Technology

2016-08-24

property for materials used in third- generation solar cells and photodetectors, among other optoelectronic devices.1−3 Unfortunately, techno- logical...detailed mechanism of iSF and to establish its relationship to chemical structure. Current literature on the mechanism of xSF is in general agreement...not been identified. We use this ring-breathing mode to generate a two- dimensional potential energy surface (PES) for the excited states along the

The 2007 Surge in Iraq: An Alternative View

DTIC Science & Technology

2014-11-01

la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2014 DRDC-RDDC-2014-R105 i Abstract...9 Figure 4 US, international (coalition partners), and ISF troop strength. . . . . . . . . . . . . . . . . 14 Figure 5 Sum of monthly SIGACT...Testing the Surge: Why Did Violence Decline in Iraq in 2007?” International Security, 37(1), (2012), pp. 7–40. 9 A SIGACT usually refers to

Verifying and Postprocesing the Ensemble Spread-Error Relationship

NASA Astrophysics Data System (ADS)

Hopson, Tom; Knievel, Jason; Liu, Yubao; Roux, Gregory; Wu, Wanli

2013-04-01

With the increased utilization of ensemble forecasts in weather and hydrologic applications, there is a need to verify their benefit over less expensive deterministic forecasts. One such potential benefit of ensemble systems is their capacity to forecast their own forecast error through the ensemble spread-error relationship. The paper begins by revisiting the limitations of the Pearson correlation alone in assessing this relationship. Next, we introduce two new metrics to consider in assessing the utility an ensemble's varying dispersion. We argue there are two aspects of an ensemble's dispersion that should be assessed. First, and perhaps more fundamentally: is there enough variability in the ensembles dispersion to justify the maintenance of an expensive ensemble prediction system (EPS), irrespective of whether the EPS is well-calibrated or not? To diagnose this, the factor that controls the theoretical upper limit of the spread-error correlation can be useful. Secondly, does the variable dispersion of an ensemble relate to variable expectation of forecast error? Representing the spread-error correlation in relation to its theoretical limit can provide a simple diagnostic of this attribute. A context for these concepts is provided by assessing two operational ensembles: 30-member Western US temperature forecasts for the U.S. Army Test and Evaluation Command and 51-member Brahmaputra River flow forecasts of the Climate Forecast and Applications Project for Bangladesh. Both of these systems utilize a postprocessing technique based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. In addition, the methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. We will describe both ensemble systems briefly, review the steps used to calibrate the ensemble forecast, and present verification statistics using error-spread metrics, along with figures from operational ensemble forecasts before and after calibration.

Analyses and forecasts of a tornadic supercell outbreak using a 3DVAR system ensemble

NASA Astrophysics Data System (ADS)

Zhuang, Zhaorong; Yussouf, Nusrat; Gao, Jidong

2016-05-01

As part of NOAA's "Warn-On-Forecast" initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.

WOD - Weather On Demand forecasting system

NASA Astrophysics Data System (ADS)

Rognvaldsson, Olafur; Ragnarsson, Logi; Stanislawska, Karolina

2017-04-01

The backbone of the Belgingur forecasting system (called WOD - Weather On Demand) is the WRF-Chem atmospheric model, with a number of in-house customisations. Initial and boundary data are taken from the Global Forecasting System, operated by the National Oceanic and Atmospheric Administration (NOAA). Operational forecasts use cycling of a number of parameters, mainly deep soil and surface fields. This is done to minimise spin-up effects and to ensure proper book-keeping of hydrological fields such as snow accumulation and runoff, as well as the constituents of various chemical parameters. The WOD system can be used to create conventional short- to medium-range weather forecasts for any location on the globe. The WOD system can also be used for air quality purposes (e.g. dispersion forecasts from volcanic eruptions) and as a tool to provide input to other modelling systems, such as hydrological models. A wide variety of post-processing options are also available, making WOD an ideal tool for creating highly customised output that can be tailored to the specific needs of individual end-users. The most recent addition to the WOD system is an integrated verification system where forecasts can be compared to surface observations from chosen locations. Forecast visualisation, such as weather charts, meteograms, weather icons and tables, is done via number of web components that can be configured to serve the varying needs of different end-users. The WOD system itself can be installed in an automatic way on hardware running a range of Linux based OS. System upgrades can also be done in semi-automatic fashion, i.e. upgrades and/or bug-fixes can be pushed to the end-user hardware without system downtime. Importantly, the WOD system requires only rudimentary knowledge of the WRF modelling, and the Linux operating systems on behalf of the end-user, making it an ideal NWP tool in locations with limited IT infrastructure.

Comparison of Observation Impacts in Two Forecast Systems using Adjoint Methods

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Langland, Rolf; Todling, Ricardo

2009-01-01

An experiment is being conducted to compare directly the impact of all assimilated observations on short-range forecast errors in different operational forecast systems. We use the adjoint-based method developed by Langland and Baker (2004), which allows these impacts to be efficiently calculated. This presentation describes preliminary results for a "baseline" set of observations, including both satellite radiances and conventional observations, used by the Navy/NOGAPS and NASA/GEOS-5 forecast systems for the month of January 2007. In each system, about 65% of the total reduction in 24-h forecast error is provided by satellite observations, although the impact of rawinsonde, aircraft, land, and ship-based observations remains significant. Only a small majority (50- 55%) of all observations assimilated improves the forecast, while the rest degrade it. It is found that most of the total forecast error reduction comes from observations with moderate-size innovations providing small to moderate impacts, not from outliers with very large positive or negative innovations. In a global context, the relative impacts of the major observation types are fairly similar in each system, although regional differences in observation impact can be significant. Of particular interest is the fact that while satellite radiances have a large positive impact overall, they degrade the forecast in certain locations common to both systems, especially over land and ice surfaces. Ongoing comparisons of this type, with results expected from other operational centers, should lead to more robust conclusions about the impacts of the various components of the observing system as well as about the strengths and weaknesses of the methodologies used to assimilate them.

How do I know if my forecasts are better? Using benchmarks in hydrological ensemble prediction

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Ramos, M. H.; Cloke, H. L.; Wetterhall, F.; Alfieri, L.; Bogner, K.; Mueller, A.; Salamon, P.

2015-03-01

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are 'toughest to beat' and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better.

Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

NASA Astrophysics Data System (ADS)

Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

2015-04-01

The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful between the 5th and the 8th day of the prediction. The information obtained is then included in an early warning system, designed in the framework of the European project iCoast (ECHO/SUB/2013/661009) with the aim of set alarms in coastal areas depending on the wave conditions, the sea level, the flooding and the run up in the coast.

Improved regional water management utilizing climate forecasts: An interbasin transfer model with a risk management framework

NASA Astrophysics Data System (ADS)

Li, Weihua; Sankarasubramanian, A.; Ranjithan, R. S.; Brill, E. D.

2014-08-01

Regional water supply systems undergo surplus and deficit conditions due to differences in inflow characteristics as well as due to their seasonal demand patterns. This study proposes a framework for regional water management by proposing an interbasin transfer (IBT) model that uses climate-information-based inflow forecast for minimizing the deviations from the end-of-season target storage across the participating pools. Using the ensemble streamflow forecast, the IBT water allocation model was applied for two reservoir systems in the North Carolina Triangle Area. Results show that interbasin transfers initiated by the ensemble streamflow forecast could potentially improve the overall water supply reliability as the demand continues to grow in the Triangle Area. To further understand the utility of climate forecasts in facilitating IBT under different spatial correlation structures between inflows and between the initial storages of the two systems, a synthetic experiment was designed to evaluate the framework under inflow forecast having different skills. Findings from the synthetic study can be summarized as follows: (a) inflow forecasts combined with the proposed IBT optimization model provide improved allocation in comparison to the allocations obtained under the no-transfer scenario as well as under transfers obtained with climatology; (b) spatial correlations between inflows and between initial storages among participating reservoirs could also influence the potential benefits that could be achieved through IBT; (c) IBT is particularly beneficial for systems that experience low correlations between inflows or between initial storages or on both attributes of the regional water supply system. Thus, if both infrastructure and permitting structures exist for promoting interbasin transfers, season-ahead inflow forecasts could provide added benefits in forecasting surplus/deficit conditions among the participating pools in the regional water supply system.

Improved Regional Water Management Utilizing Climate Forecasts: An Inter-basin Transfer Model with a Risk Management Framework

NASA Astrophysics Data System (ADS)

Li, W.; Arumugam, S.; Ranjithan, R. S.; Brill, E. D., Jr.

2014-12-01

Regional water supply systems undergo surplus and deficit conditions due to differences in inflow characteristics as well as due to their seasonal demand patterns. This study presents a framework for regional water management by proposing an Inter-Basin Transfer (IBT) model that uses climate-information-based inflow forecast for minimizing the deviations from the end- of-season target storage across the participating reservoirs. Using the ensemble streamflow forecast, the IBT water allocation model was applied for two reservoir systems in the North Carolina Triangle area. Results show that inter-basin transfers initiated by the ensemble streamflow forecast could potentially improve the overall water supply reliability as the demand continues to grow in the Triangle Area. To further understand the utility of climate forecasts in facilitating IBT under different spatial correlation structures between inflows and between the initial storages of the two systems, a synthetic experiment was designed to evaluate the framework under inflow forecast having different skills. Findings from the synthetic study can be summarized as follows: (a) Inflow forecasts combined with the proposed IBT optimization model provide improved allocation in comparison to the allocations obtained under the no- transfer scenario as well as under transfers obtained with climatology; (b) Spatial correlations between inflows and between initial storages among participating reservoirs could also influence the potential benefits that could be achieved through IBT; (c) IBT is particularly beneficial for systems that experience low correlations between inflows or between initial storages or on both attributes of the regional water supply system. Thus, if both infrastructure and permitting structures exist for promoting inter-basin transfers, season-ahead inflow forecasts could provide added benefits in forecasting surplus/deficit conditions among the participating reservoirs in the regional water supply system.

Validation of the CME Geomagnetic Forecast Alerts Under the COMESEP Alert System

NASA Astrophysics Data System (ADS)

Dumbović, Mateja; Srivastava, Nandita; Rao, Yamini K.; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

2017-08-01

Under the European Union 7th Framework Programme (EU FP7) project Coronal Mass Ejections and Solar Energetic Particles (COMESEP, http://comesep.aeronomy.be), an automated space weather alert system has been developed to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. The COMESEP alert system uses the automated detection tool called Computer Aided CME Tracking (CACTus) to detect potentially threatening CMEs, a drag-based model (DBM) to predict their arrival, and a CME geoeffectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, the DBM calculates its arrival time at Earth and the CGFT calculates its geomagnetic risk level. The geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geoeffectiveness, as well as an estimate of the geomagnetic storm duration. We present the evaluation of the CME risk level forecast with the COMESEP alert system based on a study of geoeffective CMEs observed during 2014. The validation of the forecast tool is made by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of the DBM and CGFT (independent tools available at the Hvar Observatory website, http://oh.geof.unizg.hr). The results indicate that the success rate of the forecast in its current form is unacceptably low for a realistic operation system. Human intervention improves the forecast, but the false-alarm rate remains unacceptably high. We discuss these results and their implications for possible improvement of the COMESEP alert system.

An Integrated Urban Flood Analysis System in South Korea

NASA Astrophysics Data System (ADS)

Moon, Young-Il; Kim, Min-Seok; Yoon, Tae-Hyung; Choi, Ji-Hyeok

2017-04-01

Due to climate change and the rapid growth of urbanization, the frequency of concentrated heavy rainfall has caused urban floods. As a result, we studied climate change in Korea and developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting in urban areas. This system supports synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information. As part of the measures to deal with the increase of inland flood damage, we have found it necessary to build a systematic city flood prevention system that systematizes technology to quantify flood risk as well as flood forecast, taking into consideration both inland and river water. This combined inland-river flood analysis system conducts prediction on flash rain or short-term rainfall by using radar and satellite information and performs prompt and accurate prediction on the inland flooded area. In addition, flood forecasts should be accurate and immediate. Accurate flood forecasts signify that the prediction of the watch, warning time and water level is precise. Immediate flood forecasts represent the forecasts lead time which is the time needed to evacuate. Therefore, in this study, in order to apply rainfall-runoff method to medium and small urban stream for flood forecasts, short-term rainfall forecasting using radar is applied to improve immediacy. Finally, it supports synthetic decision-making for prevention of flood disaster through real-time monitoring. Keywords: Urban Flood, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This research was supported by a grant (16AWMP-B066744-04) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Forecasting the short-term passenger flow on high-speed railway with neural networks.

PubMed

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway.

NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

NASA Astrophysics Data System (ADS)

Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

2016-12-01

Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

Forecasting the spatial transmission of influenza in the United States.

PubMed

Pei, Sen; Kandula, Sasikiran; Yang, Wan; Shaman, Jeffrey

2018-03-13

Recurrent outbreaks of seasonal and pandemic influenza create a need for forecasts of the geographic spread of this pathogen. Although it is well established that the spatial progression of infection is largely attributable to human mobility, difficulty obtaining real-time information on human movement has limited its incorporation into existing infectious disease forecasting techniques. In this study, we develop and validate an ensemble forecast system for predicting the spatiotemporal spread of influenza that uses readily accessible human mobility data and a metapopulation model. In retrospective state-level forecasts for 35 US states, the system accurately predicts local influenza outbreak onset,-i.e., spatial spread, defined as the week that local incidence increases above a baseline threshold-up to 6 wk in advance of this event. In addition, the metapopulation prediction system forecasts influenza outbreak onset, peak timing, and peak intensity more accurately than isolated location-specific forecasts. The proposed framework could be applied to emergent respiratory viruses and, with appropriate modifications, other infectious diseases.

Statistical Analysis of Atmospheric Forecast Model Accuracy - A Focus on Multiple Atmospheric Variables and Location-Based Analysis

DTIC Science & Technology

2014-04-01

WRF ) model is a numerical weather prediction system designed for operational forecasting and atmospheric research. This report examined WRF model... WRF , weather research and forecasting, atmospheric effects 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF...and Forecasting ( WRF ) model. The authors would also like to thank Ms. Sherry Larson, STS Systems Integration, LLC, ARL Technical Publishing Branch

An experimental system for flood risk forecasting and monitoring at global scale

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Alfieri, Lorenzo; Kalas, Milan; Lorini, Valerio; Salamon, Peter

2017-04-01

Global flood forecasting and monitoring systems are nowadays a reality and are being applied by a wide range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasting, combining streamflow estimations with expected inundated areas and flood impacts. Finally, emerging technologies such as crowdsourcing and social media monitoring can play a crucial role in flood disaster management and preparedness. Here, we present some recent advances of an experimental procedure for near-real time flood mapping and impact assessment. The procedure translates in near real-time the daily streamflow forecasts issued by the Global Flood Awareness System (GloFAS) into event-based flood hazard maps, which are then combined with exposure and vulnerability information at global scale to derive risk forecast. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To increase the reliability of our forecasts we propose the integration of model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification and correction of impact forecasts. Finally, we present the results of preliminary tests which show the potential of the proposed procedure in supporting emergency response and management.

Skilful seasonal forecasts of streamflow over Europe?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian

2018-04-01

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.

The FireWork air quality forecast system with near-real-time biomass burning emissions: Recent developments and evaluation of performance for the 2015 North American wildfire season.

PubMed

Pavlovic, Radenko; Chen, Jack; Anderson, Kerry; Moran, Michael D; Beaulieu, Paul-André; Davignon, Didier; Cousineau, Sophie

2016-09-01

Environment and Climate Change Canada's FireWork air quality (AQ) forecast system for North America with near-real-time biomass burning emissions has been running experimentally during the Canadian wildfire season since 2013. The system runs twice per day with model initializations at 00 UTC and 12 UTC, and produces numerical AQ forecast guidance with 48-hr lead time. In this work we describe the FireWork system, which incorporates near-real-time biomass burning emissions based on the Canadian Wildland Fire Information System (CWFIS) as an input to the operational Regional Air Quality Deterministic Prediction System (RAQDPS). To demonstrate the capability of the system we analyzed two forecast periods in 2015 (June 2-July 15, and August 15-31) when fire activity was high, and observed fire-smoke-impacted areas in western Canada and the western United States. Modeled PM2.5 surface concentrations were compared with surface measurements and benchmarked with results from the operational RAQDPS, which did not consider near-real-time biomass burning emissions. Model performance statistics showed that FireWork outperformed RAQDPS with improvements in forecast hourly PM2.5 across the region; the results were especially significant for stations near the path of fire plume trajectories. Although the hourly PM2.5 concentrations predicted by FireWork still displayed bias for areas with active fires for these two periods (mean bias [MB] of -7.3 µg m(-3) and 3.1 µg m(-3)), it showed better forecast skill than the RAQDPS (MB of -11.7 µg m(-3) and -5.8 µg m(-3)) and demonstrated a greater ability to capture temporal variability of episodic PM2.5 events (correlation coefficient values of 0.50 and 0.69 for FireWork compared to 0.03 and 0.11 for RAQDPS). A categorical forecast comparison based on an hourly PM2.5 threshold of 30 µg m(-3) also showed improved scores for probability of detection (POD), critical success index (CSI), and false alarm rate (FAR). Smoke from wildfires can have a large impact on regional air quality (AQ) and can expose populations to elevated pollution levels. Environment and Climate Change Canada has been producing operational air quality forecasts for all of Canada since 2009 and is now working to include near-real-time wildfire emissions (NRTWE) in its operational AQ forecasting system. An experimental forecast system named FireWork, which includes NRTWE, has been undergoing testing and evaluation since 2013. A performance analysis of FireWork forecasts for the 2015 wildfire season shows that FireWork provides significant improvements to surface PM2.5 forecasts and valuable guidance to regional forecasters and first responders.

An investigation into incident duration forecasting for FleetForward

DOT National Transportation Integrated Search

2000-08-01

Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...

Satellite provided fixed communications services: A forecast of potential domestic demand through the year 2000: Volume 2: Main text

NASA Technical Reports Server (NTRS)

Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

1983-01-01

Potential satellite-provided fixed communications services, baseline forecasts, net long haul forecasts, cost analysis, net addressable forecasts, capacity requirements, and satellite system market development are considered.

Scientific assessment of accuracy, skill and reliability of ocean probabilistic forecast products.

NASA Astrophysics Data System (ADS)

Wei, M.; Rowley, C. D.; Barron, C. N.; Hogan, P. J.

2016-02-01

As ocean operational centers are increasingly adopting and generating probabilistic forecast products for their customers with valuable forecast uncertainties, how to assess and measure these complicated probabilistic forecast products objectively is challenging. The first challenge is how to deal with the huge amount of the data from the ensemble forecasts. The second one is how to describe the scientific quality of probabilistic products. In fact, probabilistic forecast accuracy, skills, reliability, resolutions are different attributes of a forecast system. We briefly introduce some of the fundamental metrics such as the Reliability Diagram, Reliability, Resolution, Brier Score (BS), Brier Skill Score (BSS), Ranked Probability Score (RPS), Ranked Probability Skill Score (RPSS), Continuous Ranked Probability Score (CRPS), and Continuous Ranked Probability Skill Score (CRPSS). The values and significance of these metrics are demonstrated for the forecasts from the US Navy's regional ensemble system with different ensemble members. The advantages and differences of these metrics are studied and clarified.

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

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

Zhang, J.; Hodge, B. M.; Florita, A.

2013-10-01

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The resultsmore » show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.« less

A Solar Time-Based Analog Ensemble Method for Regional Solar Power Forecasting

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

Hodge, Brian S; Zhang, Xinmin; Li, Yuan

This paper presents a new analog ensemble method for day-ahead regional photovoltaic (PV) power forecasting with hourly resolution. By utilizing open weather forecast and power measurement data, this prediction method is processed within a set of historical data with similar meteorological data (temperature and irradiance), and astronomical date (solar time and earth declination angle). Further, clustering and blending strategies are applied to improve its accuracy in regional PV forecasting. The robustness of the proposed method is demonstrated with three different numerical weather prediction models, the North American Mesoscale Forecast System, the Global Forecast System, and the Short-Range Ensemble Forecast, formore » both region level and single site level PV forecasts. Using real measured data, the new forecasting approach is applied to the load zone in Southeastern Massachusetts as a case study. The normalized root mean square error (NRMSE) has been reduced by 13.80%-61.21% when compared with three tested baselines.« less

The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers

NASA Astrophysics Data System (ADS)

Foster, Kean; Bertacchi Uvo, Cintia; Olsson, Jonas

2018-05-01

Hydropower makes up nearly half of Sweden's electrical energy production. However, the distribution of the water resources is not aligned with demand, as most of the inflows to the reservoirs occur during the spring flood period. This means that carefully planned reservoir management is required to help redistribute water resources to ensure optimal production and accurate forecasts of the spring flood volume (SFV) is essential for this. The current operational SFV forecasts use a historical ensemble approach where the HBV model is forced with historical observations of precipitation and temperature. In this work we develop and test a multi-model prototype, building on previous work, and evaluate its ability to forecast the SFV in 84 sub-basins in northern Sweden. The hypothesis explored in this work is that a multi-model seasonal forecast system incorporating different modelling approaches is generally more skilful at forecasting the SFV in snow dominated regions than a forecast system that utilises only one approach. The testing is done using cross-validated hindcasts for the period 1981-2015 and the results are evaluated against both climatology and the current system to determine skill. Both the multi-model methods considered showed skill over the reference forecasts. The version that combined the historical modelling chain, dynamical modelling chain, and statistical modelling chain performed better than the other and was chosen for the prototype. The prototype was able to outperform the current operational system 57 % of the time on average and reduce the error in the SFV by ˜ 6 % across all sub-basins and forecast dates.

Seasonal forecasting of groundwater levels in natural aquifers in the United Kingdom

NASA Astrophysics Data System (ADS)

Mackay, Jonathan; Jackson, Christopher; Pachocka, Magdalena; Brookshaw, Anca; Scaife, Adam

2014-05-01

Groundwater aquifers comprise the world's largest freshwater resource and provide resilience to climate extremes which could become more frequent under future climate changes. Prolonged dry conditions can induce groundwater drought, often characterised by significantly low groundwater levels which may persist for months to years. In contrast, lasting wet conditions can result in anomalously high groundwater levels which result in flooding, potentially at large economic cost. Using computational models to produce groundwater level forecasts allows appropriate management strategies to be considered in advance of extreme events. The majority of groundwater level forecasting studies to date use data-based models, which exploit the long response time of groundwater levels to meteorological drivers and make forecasts based only on the current state of the system. Instead, seasonal meteorological forecasts can be used to drive hydrological models and simulate groundwater levels months into the future. Such approaches have not been used in the past due to a lack of skill in these long-range forecast products. However systems such as the latest version of the Met Office Global Seasonal Forecast System (GloSea5) are now showing increased skill up to a 3-month lead time. We demonstrate the first groundwater level ensemble forecasting system using a multi-member ensemble of hindcasts from GloSea5 between 1996 and 2009 to force 21 simple lumped conceptual groundwater models covering most of the UK's major aquifers. We present the results from this hindcasting study and demonstrate that the system can be used to forecast groundwater levels with some skill up to three months into the future.

Exploring the Virchow–Robin spaces function: A unified theory of brain diseases

PubMed Central

Cherian, Iype; Beltran, Margarita; Kasper, Ekkehard M.; Bhattarai, Binod; Munokami, Sunil; Grasso, Giovanni

2016-01-01

Background: Cerebrospinal fluid (CSF) transport across the central nervous system (CNS) is no longer believed to be on the conventional lines. The Virchow–Robin space (VRS) that facilitates CSF transport from the basal cisterns into the brain interstitial fluid (ISF) has gained interest in a whole new array of studies. Moreover, new line of evidence suggests that VRS may be involved in different pathological mechanisms of brain diseases. Methods: Here, we review emerging studies proving the feasible role of VRS in sleep, Alzheimer's disease, chronic traumatic encephalopathy, and traumatic brain injury (TBI). Results: In this study, we have outlined the possible role of VRS in different pathological conditions. Conclusion: The new insights into the physiology of the CSF circulation may have important clinical relevance for understanding the mechanisms underlying brain pathologies and their cure. PMID:27857861

Operational water management of Rijnland water system and pilot of ensemble forecasting system for flood control

NASA Astrophysics Data System (ADS)

van der Zwan, Rene

2013-04-01

The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water management, including temporary lower storage basin levels and a reduction in extra investments for infrastructural measures.

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

ENSO Prediction in the NASA GMAO GEOS-5 Seasonal Forecasting System

NASA Astrophysics Data System (ADS)

Kovach, R. M.; Borovikov, A.; Marshak, J.; Pawson, S.; Vernieres, G.

2016-12-01

Seasonal-to-Interannual coupled forecasts are conducted in near-real time with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model (AOGCM). A 30-year suite of 9-month hindcasts is available, initialized with the MERRA-Ocean, MERRA-Land, and MERRA atmospheric fields. These forecasts are used to predict the timing and magnitude of ENSO and other short-term climate variability. The 2015 El Niño peaked in November 2015 and was considered a "very strong" event with the Equatorial Pacific Ocean sea-surface-temperature (SST) anomalies higher than 2.0 °C. These very strong temperature anomalies began in Sep/Oct/Nov (SON) of 2015 and persisted through Dec/Jan/Feb (DJF) of 2016. The other two very strong El Niño events recently recorded occurred in 1981/82 and 1997/98. The GEOS-5 system began predicting a very strong El Niño for SON starting with the March 2015 forecast. At this time, the GMAO forecast was an outlier in both the NMME and IRI multi-model ensemble prediction plumes. The GMAO May 2015 forecast for the November 2015 peak in temperature anomaly in the Niño3.4 region was in excellent agreement with the real event, but in May this forecast was still one of the outliers in the multi-model forecasts. The GEOS-5 May 2015 forecast also correctly predicted the weakening of the Eastern Pacific (Niño1+2) anomalies for SON. We will present a summary of the NASA GMAO GEOS-5 Seasonal Forecast System skills based on historic hindcasts. Initial conditions, prediction of ocean surface and subsurface evolution for the 2015/16 El Niño will be compared to the 1998/97 event. GEOS-5 capability to predict the precipitation, i.e. to model the teleconnection patterns associated with El Niño will also be shown. To conclude, we will highlight some new developments in the GEOS forecasting system.

Against all odds -- Probabilistic forecasts and decision making

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

Evaluation of Clear-Air Turbulence Diagnostics: GTG in Korea

NASA Astrophysics Data System (ADS)

Kim, J.-H.; Chun, H.-Y.; Jang, W.; Sharman, R. D.

2009-04-01

Turbulence forecasting algorithm, the Graphical Turbulence Guidance (GTG) system developed at NCAR (Sharman et al., 2006), is evaluated with available turbulence observations (e.g. pilot reports; PIREPs) reported in South Korea during the recent 4 years (2003-2007). Clear-air turbulence (CAT) is extracted from PIREPs by using cloud-to-ground lightning flash data from Korean Meteorological Administration (KMA). The GTG system includes several steps. First, 45 turbulence indices are calculated in the East Asian region near Korean peninsula using the Regional Data Assimilation and Prediction System (RDAPS) analysis data with 30 km horizontal grid spacing provided by KMA. Second, 10 CAT indices that performed ten best forecasting score are selected. The scoring method is based on the probability of detection, which is calculated using PIREPs exclusively of moderate-or-greater intensity. Various statistical examinations and sensitivity tests of the GTG system are performed by yearly and seasonally classified PIREPs in South Korea. Performance of GTG is more consistent and stable than that of any individual diagnostic in each year and season. In addition, current-year forecasting based on yearly PIREPs is better than adjacent-year forecasting and year-after-year forecasting. Seasonal forecasting is generally better than yearly forecasting, because selected CAT indices in each season represent meteorological condition much more properly than applying the selected CAT indices to all seasons. Wintertime forecasting is the best among the four seasonal forecastings. This is likely due to that the GTG system consists of many CAT indices related to jet stream, and turbulence associated with the jet can be most activated in wintertime under strong jet magnitude. On the other hand, summertime forecasting skill is much less than in wintertime. To acquire better performance for summertime forecasting, it is likely to develop more turbulence indices related to, for example, convections. By sensitivity test to the number of combined indices, it is found that yearly and seasonal GTG is the best when about 7 CAT indices are combined.

Some economic benefits of a synchronous earth observatory satellite

NASA Technical Reports Server (NTRS)

Battacharyya, R. K.; Greenberg, J. S.; Lowe, D. S.; Sattinger, I. J.

1974-01-01

An analysis was made of the economic benefits which might be derived from reduced forecasting errors made possible by data obtained from a synchronous satellite system which can collect earth observation and meteorological data continuously and on demand. User costs directly associated with achieving benefits are included. In the analysis, benefits were evaluated which might be obtained as a result of improved thunderstorm forecasting, frost warning, and grain harvest forecasting capabilities. The anticipated system capabilities were used to arrive at realistic estimates of system performance on which to base the benefit analysis. Emphasis was placed on the benefits which result from system forecasting accuracies. Benefits from improved thunderstorm forecasts are indicated for the construction, air transportation, and agricultural industries. The effects of improved frost warning capability on the citrus crop are determined. The benefits from improved grain forecasting capability are evaluated in terms of both U.S. benefits resulting from domestic grain distribution and U.S. benefits from international grain distribution.

Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

NASA Astrophysics Data System (ADS)

Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

2018-01-01

Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

Human-model hybrid Korean air quality forecasting system.

PubMed

Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

2016-09-01

The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.

Optimising seasonal streamflow forecast lead time for operational decision making in Australia

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul

2016-10-01

Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.

Real-time Social Internet Data to Guide Forecasting Models

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

Del Valle, Sara Y.

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematicalmore » approaches and heterogeneous data streams.« less

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

NASA Astrophysics Data System (ADS)

Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

2018-03-01

Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

Flood Forecast Accuracy and Decision Support System Approach: the Venice Case

NASA Astrophysics Data System (ADS)

Canestrelli, A.; Di Donato, M.

2016-02-01

In the recent years numerical models for weather predictions have experienced continuous advances in technology. As a result, all the disciplines making use of weather forecasts have made significant steps forward. In the case of the Safeguard of Venice, a large effort has been put in order to improve the forecast of tidal levels. In this context, the Istituzione Centro Previsioni e Segnalazioni Maree (ICPSM) of the Venice Municipality has developed and tested many different forecast models, both of the statistical and deterministic type, and has shown to produce very accurate forecasts. For Venice, the maximum admissible forecast error should be (ideally) of the order of ten centimeters at 24 hours. The entity of the forecast error clearly affects the decisional process, which mainly consists of alerting the population, activating the movable barriers installed at the three tidal inlets and contacting the port authority. This process becomes more challenging whenever the weather predictions, and therefore the water level forecasts, suddenly change. These new forecasts have to be quickly transformed into operational tasks. Therefore, it is of the utter importance to set up scheduled alerts and emergency plans by means of easy-to-follow procedures. On this direction, Technital has set up a Decision Support System based on expert procedures that minimizes the human mistakes and, as a consequence, reduces the risk of flooding of the historical center. Moreover, the Decision Support System can communicate predefined alerts to all the interested subjects. The System uses the water levels forecasts produced by the ICPSM by taking into account the accuracy at different leading times. The Decision Support System has been successfully tested with 8 years of data, 6 of them in real time. Venice experience shows that the Decision Support System is an essential tool which assesses the risks associated with a particular event, provides clear operational procedures and minimizes the impact of natural floods on human lives, private properties and historical monuments.

Multi-RCM ensemble downscaling of global seasonal forecasts (MRED)

NASA Astrophysics Data System (ADS)

Arritt, R. W.

2008-12-01

The Multi-RCM Ensemble Downscaling (MRED) project was recently initiated to address the question, Can regional climate models provide additional useful information from global seasonal forecasts? MRED will use a suite of regional climate models to downscale seasonal forecasts produced by the new National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) seasonal forecast system and the NASA GEOS5 system. The initial focus will be on wintertime forecasts in order to evaluate topographic forcing, snowmelt, and the potential usefulness of higher resolution, especially for near-surface fields influenced by high resolution orography. Each regional model will cover the conterminous US (CONUS) at approximately 32 km resolution, and will perform an ensemble of 15 runs for each year 1982-2003 for the forecast period 1 December - 30 April. MRED will compare individual regional and global forecasts as well as ensemble mean precipitation and temperature forecasts, which are currently being used to drive macroscale land surface models (LSMs), as well as wind, humidity, radiation, turbulent heat fluxes, which are important for more advanced coupled macro-scale hydrologic models. Metrics of ensemble spread will also be evaluated. Extensive analysis will be performed to link improvements in downscaled forecast skill to regional forcings and physical mechanisms. Our overarching goal is to determine what additional skill can be provided by a community ensemble of high resolution regional models, which we believe will eventually define a strategy for more skillful and useful regional seasonal climate forecasts.

Regional Model Nesting Within GFS Daily Forecasts Over West Africa

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.; Fulakeza, Matthew; Lonergan, Patrick; Worrell, Ruben

2010-01-01

The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger is shown.

A seasonal agricultural drought forecast system for food-insecure regions of East Africa

USGS Publications Warehouse

Shukla, Shraddhanand; McNally, Amy; Husak, Gregory; Funk, Christopher C.

2014-01-01

 The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is critical for end-of-season outcomes. Finally we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (> 0.8 correlation) during drought years. This means that this system might be particularity useful for identifying the events that present the greatest risk to the region.

Remote Sensing and River Discharge Forecasting for Major Rivers in South Asia (Invited)

NASA Astrophysics Data System (ADS)

Webster, P. J.; Hopson, T. M.; Hirpa, F. A.; Brakenridge, G. R.; De-Groeve, T.; Shrestha, K.; Gebremichael, M.; Restrepo, P. J.

2013-12-01

The South Asia is a flashpoint for natural disasters particularly flooding of the Indus, Ganges, and Brahmaputra has profound societal impacts for the region and globally. The 2007 Brahmaputra floods affecting India and Bangladesh, the 2008 avulsion of the Kosi River in India, the 2010 flooding of the Indus River in Pakistan and the 2013 Uttarakhand exemplify disasters on scales almost inconceivable elsewhere. Their frequent occurrence of floods combined with large and rapidly growing populations, high levels of poverty and low resilience, exacerbate the impact of the hazards. Mitigation of these devastating hazards are compounded by limited flood forecast capability, lack of rain/gauge measuring stations and forecast use within and outside the country, and transboundary data sharing on natural hazards. Here, we demonstrate the utility of remotely-derived hydrologic and weather products in producing skillful flood forecasting information without reliance on vulnerable in situ data sources. Over the last decade a forecast system has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers in Bangldesh was developed (Hopson and Webster 2010). The system utilizes ECMWF weather forecast uncertainty information and ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates, together with the limited near-real-time river stage observations from Bangladesh. This system has been expanded to Pakistan and has successfully forecast the 2010-2012 flooding (Shrestha and Webster 2013). To overcome the in situ hydrological data problem, recent efforts in parallel with the numerical modeling have utilized microwave satellite remote sensing of river widths to generate operational discharge advective-based forecasts for the Ganges and Brahmaputra. More than twenty remotely locations upstream of Bangldesh were used to produce stand-alone river flow nowcasts and forecasts at 1-15 days lead time. showing that satellite-based flow estimates are a useful source of dynamical surface water information in data-scarce regions and that they could be used for model calibration and data assimilation purposes in near-time hydrologic forecast applications (Hirpa et al. 2013). More recent efforts during this year's monsoon season are optimally combining these different independent sources of river forecast information along with archived flood inundation imagery of the Dartmouth Flood Observatory to improve the visualization and overall skill of the ongoing CFAB ensemble weather forecast-based flood forecasting system within the unique context of the ongoing flood forecasting efforts for Bangladesh.

Enhanced seasonal forecast skill following stratospheric sudden warmings

NASA Astrophysics Data System (ADS)

Sigmond, M.; Scinocca, J. F.; Kharin, V. V.; Shepherd, T. G.

2013-02-01

Advances in seasonal forecasting have brought widespread socio-economic benefits. However, seasonal forecast skill in the extratropics is relatively modest, prompting the seasonal forecasting community to search for additional sources of predictability. For over a decade it has been suggested that knowledge of the state of the stratosphere can act as a source of enhanced seasonal predictability; long-lived circulation anomalies in the lower stratosphere that follow stratospheric sudden warmings are associated with circulation anomalies in the troposphere that can last up to two months. Here, we show by performing retrospective ensemble model forecasts that such enhanced predictability can be realized in a dynamical seasonal forecast system with a good representation of the stratosphere. When initialized at the onset date of stratospheric sudden warmings, the model forecasts faithfully reproduce the observed mean tropospheric conditions in the months following the stratospheric sudden warmings. Compared with an equivalent set of forecasts that are not initialized during stratospheric sudden warmings, we document enhanced forecast skill for atmospheric circulation patterns, surface temperatures over northern Russia and eastern Canada and North Atlantic precipitation. We suggest that seasonal forecast systems initialized during stratospheric sudden warmings are likely to yield significantly greater forecast skill in some regions.

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

A PERFORMANCE EVALUATION OF THE ETA- CMAQ AIR QUALITY FORECAST SYSTEM FOR THE SUMMER OF 2005

EPA Science Inventory

This poster presents an evaluation of the Eta-CMAQ Air Quality Forecast System's experimental domain using O₃ observations obtained from EPA's AIRNOW program and a suite of statistical metrics examining both discrete and categorical forecasts.

System load forecasts for an electric utility. [Hourly loads using Box-Jenkins method

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

Uri, N.D.

This paper discusses forecasting hourly system load for an electric utility using Box-Jenkins time-series analysis. The results indicate that a model based on the method of Box and Jenkins, given its simplicity, gives excellent results over the forecast horizon.

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

Uncertainty quantification and reliability assessment in operational oil spill forecast modeling system.

PubMed

Hou, Xianlong; Hodges, Ben R; Feng, Dongyu; Liu, Qixiao

2017-03-15

As oil transport increasing in the Texas bays, greater risks of ship collisions will become a challenge, yielding oil spill accidents as a consequence. To minimize the ecological damage and optimize rapid response, emergency managers need to be informed with how fast and where oil will spread as soon as possible after a spill. The state-of-the-art operational oil spill forecast modeling system improves the oil spill response into a new stage. However uncertainty due to predicted data inputs often elicits compromise on the reliability of the forecast result, leading to misdirection in contingency planning. Thus understanding the forecast uncertainty and reliability become significant. In this paper, Monte Carlo simulation is implemented to provide parameters to generate forecast probability maps. The oil spill forecast uncertainty is thus quantified by comparing the forecast probability map and the associated hindcast simulation. A HyosPy-based simple statistic model is developed to assess the reliability of an oil spill forecast in term of belief degree. The technologies developed in this study create a prototype for uncertainty and reliability analysis in numerical oil spill forecast modeling system, providing emergency managers to improve the capability of real time operational oil spill response and impact assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

DOE PAGES

Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; ...

2015-11-10

Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

Nationwide validation of ensemble streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service

NASA Astrophysics Data System (ADS)

Lee, H. S.; Liu, Y.; Ward, J.; Brown, J.; Maestre, A.; Herr, H.; Fresch, M. A.; Wells, E.; Reed, S. M.; Jones, E.

2017-12-01

The National Weather Service's (NWS) Office of Water Prediction (OWP) recently launched a nationwide effort to verify streamflow forecasts from the Hydrologic Ensemble Forecast Service (HEFS) for a majority of forecast locations across the 13 River Forecast Centers (RFCs). Known as the HEFS Baseline Validation (BV), the project involves a joint effort between the OWP and the RFCs. It aims to provide a geographically consistent, statistically robust validation, and a benchmark to guide the operational implementation of the HEFS, inform practical applications, such as impact-based decision support services, and to provide an objective framework for evaluating strategic investments in the HEFS. For the BV, HEFS hindcasts are issued once per day on a 12Z cycle for the period of 1985-2015 with a forecast horizon of 30 days. For the first two weeks, the hindcasts are forced with precipitation and temperature ensemble forecasts from the Global Ensemble Forecast System of the National Centers for Environmental Prediction, and by resampled climatology for the remaining period. The HEFS-generated ensemble streamflow hindcasts are verified using the Ensemble Verification System. Skill is assessed relative to streamflow hindcasts generated from NWS' current operational system, namely climatology-based Ensemble Streamflow Prediction. In this presentation, we summarize the results and findings to date.

Theoretical Models for Aircraft Availability: Classical Approach to Identification of Trends, Seasonality, and System Constraints in the Development of Realized Models

DTIC Science & Technology

2004-03-01

predicting future events ( Heizer and Render , 1999). Forecasting techniques fall into two major categories, qualitative and quantitative methods...Globemaster III.” Excerpt from website. www.globalsecurity.org/military /systems/ aircraft/c-17-history.htm. 2003. Heizer , Jay, and Barry Render ...of the past data used to make the forecast ( Heizer , et. al., 1999). Explanatory forecasting models assume that the variable being forecasted

A report from the Space Science and Engineering Center, the University of Wisconsin-Madison, Madison, Wisconsin

NASA Technical Reports Server (NTRS)

1985-01-01

Operational forecasters have habitually been plagued with the problems associated with acquisition, display, and dissemination of data used in preparing forecasts. The centralized storm information system (CSIS) experiment provided an operational forecaster with an interactive computer system which could perform these preliminary tasks more quickly and accurately than any human could. CSIS objectives pertaining to improved severe storms forecasting and warning procedures are addressed.

The Implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for Global Dust Forecasting at NOAA NCEP

NASA Technical Reports Server (NTRS)

Lu, Cheng-Hsuan; Da Silva, Arlindo M.; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S.; Chen, Shen-Po; Chuang, Hui-Ya;

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

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

Hodge, B. M.; Florita, A.; Orwig, K.

2012-07-01

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent Systemmore » Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.« less

NOMADS-NOAA Operational Model Archive and Distribution System

Science.gov Websites

Forecast Maps Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library (16km) 6 hours grib filter http OpenDAP-alt URMA hourly - http - Climate Models Climate Forecast System Flux Products 6 hours grib filter http - Climate Forecast System 3D Pressure Products 6 hours grib

Impacts of Short-Term Solar Power Forecasts in System Operations

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

Ibanez, Eduardo; Krad, Ibrahim; Hodge, Bri-Mathias

2016-05-05

Solar generation is experiencing an exponential growth in power systems worldwide and, along with wind power, is posing new challenges to power system operations. Those challenges are characterized by an increase of system variability and uncertainty across many time scales: from days, down to hours, minutes, and seconds. Much of the research in the area has focused on the effect of solar forecasting across hours or days. This paper presents a methodology to capture the effect of short-term forecasting strategies and analyzes the economic and reliability implications of utilizing a simple, yet effective forecasting method for solar PV in intra-daymore » operations.« less

The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

NASA Technical Reports Server (NTRS)

Reynolds, David; Rasch, William; Kozlowski, Daniel; Burks, Jason; Zavodsky, Bradley; Bernardet, Ligia; Jankov, Isidora; Albers, Steve

2014-01-01

The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near-realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9-km horizontal grid spacing. The ensemble has eight members, all employing WRF-ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012-2013 and 2013-2014 winters. A smaller domain covering just the West Coast was created to minimize band-width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short-term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6-hr QPF along with the ExREF mean 6-hr QPF so the forecasters can build confidence in the use of the ExREF in preparing their rainfall forecasts. Preliminary results will be presented.

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

NASA Astrophysics Data System (ADS)

Hou, Tuanjie; Kong, Fanyou; Chen, Xunlai; Lei, Hengchi; Hu, Zhaoxia

2015-07-01

To improve the accuracy of short-term (0-12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System (HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting (WRF-ARW) model and the Advanced Regional Prediction System (ARPS) three-dimensional variational data assimilation (3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station (AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting (QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to 9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6-9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score (FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.

Oregon Washington Coastal Ocean Forecast System: Real-time Modeling and Data Assimilation

NASA Astrophysics Data System (ADS)

Erofeeva, S.; Kurapov, A. L.; Pasmans, I.

2016-02-01

Three-day forecasts of ocean currents, temperature and salinity along the Oregon and Washington coasts are produced daily by a numerical ROMS-based ocean circulation model. NAM is used to derive atmospheric forcing for the model. Fresh water discharge from Columbia River, Fraser River, and small rivers in Puget Sound are included. The forecast is constrained by open boundary conditions derived from the global Navy HYCOM model and once in 3 days assimilation of recent data, including HF radar surface currents, sea surface temperature from the GOES satellite, and SSH from several satellite altimetry missions. 4-dimensional variational data assimilation is implemented in 3-day time windows using the tangent linear and adjoint codes developed at OSU. The system is semi-autonomous - all the data, including NAM and HYCOM fields are automatically updated, and daily operational forecast is automatically initiated. The pre-assimilation data quality control and post-assimilation forecast quality control require the operator's involvement. The daily forecast and 60 days of hindcast fields are available for public on opendap. As part of the system model validation plots to various satellites and SEAGLIDER are also automatically updated and available on the web (http://ingria.coas.oregonstate.edu/rtdavow/). Lessons learned in this pilot real-time coastal ocean forecasting project help develop and test metrics for forecast skill assessment for the West Coast Operational Forecast System (WCOFS), currently at testing and development phase at the National Oceanic and Atmospheric Administration (NOAA).

An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Martin, J. H.

1999-07-01

A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

Stochastic Forcing for High-Resolution Regional and Global Ocean and Atmosphere-Ocean Coupled Ensemble Forecast System

NASA Astrophysics Data System (ADS)

Rowley, C. D.; Hogan, P. J.; Martin, P.; Thoppil, P.; Wei, M.

2017-12-01

An extended range ensemble forecast system is being developed in the US Navy Earth System Prediction Capability (ESPC), and a global ocean ensemble generation capability to represent uncertainty in the ocean initial conditions has been developed. At extended forecast times, the uncertainty due to the model error overtakes the initial condition as the primary source of forecast uncertainty. Recently, stochastic parameterization or stochastic forcing techniques have been applied to represent the model error in research and operational atmospheric, ocean, and coupled ensemble forecasts. A simple stochastic forcing technique has been developed for application to US Navy high resolution regional and global ocean models, for use in ocean-only and coupled atmosphere-ocean-ice-wave ensemble forecast systems. Perturbation forcing is added to the tendency equations for state variables, with the forcing defined by random 3- or 4-dimensional fields with horizontal, vertical, and temporal correlations specified to characterize different possible kinds of error. Here, we demonstrate the stochastic forcing in regional and global ensemble forecasts with varying perturbation amplitudes and length and time scales, and assess the change in ensemble skill measured by a range of deterministic and probabilistic metrics.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operatormore » can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operatormore » can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Alternative Approaches to Land Initialization for Seasonal Precipitation and Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, Randal; Suarez, Max; Liu, Ping; Jambor, Urszula

2004-01-01

The seasonal prediction system of the NASA Global Modeling and Assimilation Office is used to generate ensembles of summer forecasts utilizing realistic soil moisture initialization. To derive the realistic land states, we drive offline the system's land model with realistic meteorological forcing over the period 1979-1993 (in cooperation with the Global Land Data Assimilation System project at GSFC) and then extract the state variables' values on the chosen forecast start dates. A parallel series of forecast ensembles is performed with a random (though climatologically consistent) set of land initial conditions; by comparing the two sets of ensembles, we can isolate the impact of land initialization on forecast skill from that of the imposed SSTs. The base initialization experiment is supplemented with several forecast ensembles that use alternative initialization techniques. One ensemble addresses the impact of minimizing climate drift in the system through the scaling of the initial conditions, and another is designed to isolate the importance of the precipitation signal from that of all other signals in the antecedent offline forcing. A third ensemble includes a more realistic initialization of the atmosphere along with the land initialization. The impact of each variation on forecast skill is quantified.

Using planned adaptation to implement evidence-based programs with new populations.

PubMed

Lee, Shawna J; Altschul, Inna; Mowbray, Carol T

2008-06-01

The Interactive Systems Framework (ISF) for Dissemination and Implementation (Wandersman et al. 2008) elaborates the functions and structures that move evidence-based programs (EBPs) from research to practice. Inherent in that process is the tension between implementing programs with fidelity and the need to tailor programs to fit the target population. We propose Planned Adaptation as one approach to resolve this tension, with the goal of guiding practitioners in adapting EBPs so that they maintain core components of program theory while taking into account the needs of particular populations. Planned Adaptation is a form of capacity building within the Prevention Support System that provides a framework to guide practitioners in adapting programs while encouraging researchers to provide information relevant to adaptation as a critical aspect of dissemination research, with the goal of promoting wider dissemination and better implementation of EBPs. We illustrate Planned Adaptation using the JOBS Program (Caplan et al. 1989), which was developed for recently laid-off, working- and middle-class workers and subsequently implemented with welfare recipients.

Host Range Restriction of Insect-Specific Flaviviruses Occurs at Several Levels of the Viral Life Cycle.

PubMed

Junglen, Sandra; Korries, Marvin; Grasse, Wolfgang; Wieseler, Janett; Kopp, Anne; Hermanns, Kyra; León-Juárez, Moises; Drosten, Christian; Kümmerer, Beate Mareike

2017-01-01

The genus Flavivirus contains emerging arthropod-borne viruses (arboviruses) infecting vertebrates, as well as insect-specific viruses (ISVs) (i.e., viruses whose host range is restricted to insects). ISVs are evolutionary precursors to arboviruses. Knowledge of the nature of the ISV infection block in vertebrates could identify functions necessary for the expansion of the host range toward vertebrates. Mapping of host restrictions by complementation of ISV and arbovirus genome functions could generate knowledge critical to predicting arbovirus emergence. Here we isolated a novel flavivirus, termed Niénokoué virus (NIEV), from mosquitoes sampled in Côte d'Ivoire. NIEV groups with insect-specific flaviviruses (ISFs) in phylogeny and grows in insect cells but not in vertebrate cells. We generated an infectious NIEV cDNA clone and a NIEV reporter replicon to study growth restrictions of NIEV in comparison to yellow fever virus (YFV), for which the same tools are available. Efficient RNA replication of the NIEV reporter replicon was observed in insect cells but not in vertebrate cells. Initial translation of the input replicon RNA in vertebrate cells was functional, but RNA replication did not occur. Chimeric YFV carrying the envelope proteins of NIEV was recovered via electroporation in C6/36 insect cells but did not infect vertebrate cells, indicating a block at the level of entry. Since the YF/NIEV chimera readily produced infectious particles in insect cells but not in vertebrate cells despite efficient RNA replication, restriction is also determined at the level of assembly/release. Taking the results together, the ability of ISF to infect vertebrates is blocked at several levels, including attachment/entry and RNA replication as well as assembly/release. IMPORTANCE Most viruses of the genus Flavivirus , e.g., YFV and dengue virus, are mosquito borne and transmitted to vertebrates during blood feeding of mosquitoes. Within the last decade, an increasing number of viruses with a host range exclusively restricted to insects in close relationship to the vertebrate-pathogenic flaviviruses were discovered in mosquitoes. To identify barriers that could block the arboviral vertebrate tropism, we set out to identify the steps at which the ISF replication cycle fails in vertebrates. Our studies revealed blocks at several levels, suggesting that flavivirus host range expansion from insects to vertebrates was a complex process that involved overcoming multiple barriers.

The Effect of Body Posture on Brain Glymphatic Transport.

PubMed

Lee, Hedok; Xie, Lulu; Yu, Mei; Kang, Hongyi; Feng, Tian; Deane, Rashid; Logan, Jean; Nedergaard, Maiken; Benveniste, Helene

2015-08-05

The glymphatic pathway expedites clearance of waste, including soluble amyloid β (Aβ) from the brain. Transport through this pathway is controlled by the brain's arousal level because, during sleep or anesthesia, the brain's interstitial space volume expands (compared with wakefulness), resulting in faster waste removal. Humans, as well as animals, exhibit different body postures during sleep, which may also affect waste removal. Therefore, not only the level of consciousness, but also body posture, might affect CSF-interstitial fluid (ISF) exchange efficiency. We used dynamic-contrast-enhanced MRI and kinetic modeling to quantify CSF-ISF exchange rates in anesthetized rodents' brains in supine, prone, or lateral positions. To validate the MRI data and to assess specifically the influence of body posture on clearance of Aβ, we used fluorescence microscopy and radioactive tracers, respectively. The analysis showed that glymphatic transport was most efficient in the lateral position compared with the supine or prone positions. In the prone position, in which the rat's head was in the most upright position (mimicking posture during the awake state), transport was characterized by "retention" of the tracer, slower clearance, and more CSF efflux along larger caliber cervical vessels. The optical imaging and radiotracer studies confirmed that glymphatic transport and Aβ clearance were superior in the lateral and supine positions. We propose that the most popular sleep posture (lateral) has evolved to optimize waste removal during sleep and that posture must be considered in diagnostic imaging procedures developed in the future to assess CSF-ISF transport in humans. The rodent brain removes waste better during sleep or anesthesia compared with the awake state. Animals exhibit different body posture during the awake and sleep states, which might affect the brain's waste removal efficiency. We investigated the influence of body posture on brainwide transport of inert tracers of anesthetized rodents. The major finding of our study was that waste, including Aβ, removal was most efficient in the lateral position (compared with the prone position), which mimics the natural resting/sleeping position of rodents. Although our finding awaits testing in humans, we speculate that the lateral position during sleep has advantage with regard to the removal of waste products including Aβ, because clinical studies have shown that sleep drives Aβ clearance from the brain. Copyright © 2015 the authors 0270-6474/15/3511034-11$15.00/0.

Host Range Restriction of Insect-Specific Flaviviruses Occurs at Several Levels of the Viral Life Cycle

PubMed Central

Junglen, Sandra; Korries, Marvin; Grasse, Wolfgang; Wieseler, Janett; Kopp, Anne; Hermanns, Kyra; León-Juárez, Moises; Drosten, Christian

2017-01-01

ABSTRACT The genus Flavivirus contains emerging arthropod-borne viruses (arboviruses) infecting vertebrates, as well as insect-specific viruses (ISVs) (i.e., viruses whose host range is restricted to insects). ISVs are evolutionary precursors to arboviruses. Knowledge of the nature of the ISV infection block in vertebrates could identify functions necessary for the expansion of the host range toward vertebrates. Mapping of host restrictions by complementation of ISV and arbovirus genome functions could generate knowledge critical to predicting arbovirus emergence. Here we isolated a novel flavivirus, termed Niénokoué virus (NIEV), from mosquitoes sampled in Côte d’Ivoire. NIEV groups with insect-specific flaviviruses (ISFs) in phylogeny and grows in insect cells but not in vertebrate cells. We generated an infectious NIEV cDNA clone and a NIEV reporter replicon to study growth restrictions of NIEV in comparison to yellow fever virus (YFV), for which the same tools are available. Efficient RNA replication of the NIEV reporter replicon was observed in insect cells but not in vertebrate cells. Initial translation of the input replicon RNA in vertebrate cells was functional, but RNA replication did not occur. Chimeric YFV carrying the envelope proteins of NIEV was recovered via electroporation in C6/36 insect cells but did not infect vertebrate cells, indicating a block at the level of entry. Since the YF/NIEV chimera readily produced infectious particles in insect cells but not in vertebrate cells despite efficient RNA replication, restriction is also determined at the level of assembly/release. Taking the results together, the ability of ISF to infect vertebrates is blocked at several levels, including attachment/entry and RNA replication as well as assembly/release. IMPORTANCE Most viruses of the genus Flavivirus, e.g., YFV and dengue virus, are mosquito borne and transmitted to vertebrates during blood feeding of mosquitoes. Within the last decade, an increasing number of viruses with a host range exclusively restricted to insects in close relationship to the vertebrate-pathogenic flaviviruses were discovered in mosquitoes. To identify barriers that could block the arboviral vertebrate tropism, we set out to identify the steps at which the ISF replication cycle fails in vertebrates. Our studies revealed blocks at several levels, suggesting that flavivirus host range expansion from insects to vertebrates was a complex process that involved overcoming multiple barriers. PMID:28101536

The Effect of Body Posture on Brain Glymphatic Transport

PubMed Central

Lee, Hedok; Xie, Lulu; Yu, Mei; Kang, Hongyi; Feng, Tian; Deane, Rashid; Logan, Jean; Nedergaard, Maiken

2015-01-01

The glymphatic pathway expedites clearance of waste, including soluble amyloid β (Aβ) from the brain. Transport through this pathway is controlled by the brain's arousal level because, during sleep or anesthesia, the brain's interstitial space volume expands (compared with wakefulness), resulting in faster waste removal. Humans, as well as animals, exhibit different body postures during sleep, which may also affect waste removal. Therefore, not only the level of consciousness, but also body posture, might affect CSF–interstitial fluid (ISF) exchange efficiency. We used dynamic-contrast-enhanced MRI and kinetic modeling to quantify CSF-ISF exchange rates in anesthetized rodents' brains in supine, prone, or lateral positions. To validate the MRI data and to assess specifically the influence of body posture on clearance of Aβ, we used fluorescence microscopy and radioactive tracers, respectively. The analysis showed that glymphatic transport was most efficient in the lateral position compared with the supine or prone positions. In the prone position, in which the rat's head was in the most upright position (mimicking posture during the awake state), transport was characterized by “retention” of the tracer, slower clearance, and more CSF efflux along larger caliber cervical vessels. The optical imaging and radiotracer studies confirmed that glymphatic transport and Aβ clearance were superior in the lateral and supine positions. We propose that the most popular sleep posture (lateral) has evolved to optimize waste removal during sleep and that posture must be considered in diagnostic imaging procedures developed in the future to assess CSF-ISF transport in humans. SIGNIFICANCE STATEMENT The rodent brain removes waste better during sleep or anesthesia compared with the awake state. Animals exhibit different body posture during the awake and sleep states, which might affect the brain's waste removal efficiency. We investigated the influence of body posture on brainwide transport of inert tracers of anesthetized rodents. The major finding of our study was that waste, including Aβ, removal was most efficient in the lateral position (compared with the prone position), which mimics the natural resting/sleeping position of rodents. Although our finding awaits testing in humans, we speculate that the lateral position during sleep has advantage with regard to the removal of waste products including Aβ, because clinical studies have shown that sleep drives Aβ clearance from the brain. PMID:26245965

On the reliability of seasonal climate forecasts

PubMed Central

Weisheimer, A.; Palmer, T. N.

2014-01-01

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1–5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that ‘goodness’ should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a ‘5’ should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of ‘goodness’ rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching ‘5’ across all regions and variables in 30 years time. PMID:24789559

Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts

NASA Astrophysics Data System (ADS)

Bao, Hongjun; Zhao, Linna

2012-02-01

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

Wave ensemble forecast system for tropical cyclones in the Australian region

NASA Astrophysics Data System (ADS)

Zieger, Stefan; Greenslade, Diana; Kepert, Jeffrey D.

2018-05-01

Forecasting of waves under extreme conditions such as tropical cyclones is vitally important for many offshore industries, but there remain many challenges. For Northwest Western Australia (NW WA), wave forecasts issued by the Australian Bureau of Meteorology have previously been limited to products from deterministic operational wave models forced by deterministic atmospheric models. The wave models are run over global (resolution 1/4∘) and regional (resolution 1/10∘) domains with forecast ranges of + 7 and + 3 day respectively. Because of this relatively coarse resolution (both in the wave models and in the forcing fields), the accuracy of these products is limited under tropical cyclone conditions. Given this limited accuracy, a new ensemble-based wave forecasting system for the NW WA region has been developed. To achieve this, a new dedicated 8-km resolution grid was nested in the global wave model. Over this grid, the wave model is forced with winds from a bias-corrected European Centre for Medium Range Weather Forecast atmospheric ensemble that comprises 51 ensemble members to take into account the uncertainties in location, intensity and structure of a tropical cyclone system. A unique technique is used to select restart files for each wave ensemble member. The system is designed to operate in real time during the cyclone season providing + 10-day forecasts. This paper will describe the wave forecast components of this system and present the verification metrics and skill for specific events.

Worldwide satellite market demand forecast

NASA Technical Reports Server (NTRS)

Bowyer, J. M.; Frankfort, M.; Steinnagel, K. M.

1981-01-01

The forecast is for the years 1981 - 2000 with benchmark years at 1985, 1990 and 2000. Two typs of markets are considered for this study: Hardware (worldwide total) - satellites, earth stations and control facilities (includes replacements and spares); and non-hardware (addressable by U.S. industry) - planning, launch, turnkey systems and operations. These markets were examined for the INTELSAT System (international systems and domestic and regional systems using leased transponders) and domestic and regional systems. Forecasts were determined for six worldwide regions encompassing 185 countries using actual costs for existing equipment and engineering estimates of costs for advanced systems. Most likely (conservative growth rate estimates) and optimistic (mid range growth rate estimates) scenarios were employed for arriving at the forecasts which are presented in constant 1980 U.S. dollars. The worldwide satellite market demand forecast predicts that the market between 181 and 2000 will range from $35 to $50 billion. Approximately one-half of the world market, $16 to $20 billion, will be generated in the United States.

Current and future data assimilation development in the Copernicus Atmosphere Monitoring Service

NASA Astrophysics Data System (ADS)

Engelen, R. J.; Ades, M.; Agusti-panareda, A.; Flemming, J.; Inness, A.; Kipling, Z.; Parrington, M.; Peuch, V. H.

2017-12-01

The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The system assimilates observations from more than 60 satellite sensors to constrain both the meteorology and the atmospheric composition species. While an operational forecasting system needs to be robust and reliable, it also needs to stay state-of-the-art to provide the best possible forecasts. Continuous development is therefore an important component of the CAMS systems. We will present on-going efforts on improving the 4D-Var data assimilation system, such as using ensemble data assimilation to improve the background error covariances and more accurate use of satellite observations. We will also outline plans for including emissions in the daily CAMS analyses, which is an area where research activities have a large potential to feed into operational applications.

Worldwide satellite market demand forecast

NASA Astrophysics Data System (ADS)

Bowyer, J. M.; Frankfort, M.; Steinnagel, K. M.

1981-06-01

The forecast is for the years 1981 - 2000 with benchmark years at 1985, 1990 and 2000. Two typs of markets are considered for this study: Hardware (worldwide total) - satellites, earth stations and control facilities (includes replacements and spares); and non-hardware (addressable by U.S. industry) - planning, launch, turnkey systems and operations. These markets were examined for the INTELSAT System (international systems and domestic and regional systems using leased transponders) and domestic and regional systems. Forecasts were determined for six worldwide regions encompassing 185 countries using actual costs for existing equipment and engineering estimates of costs for advanced systems. Most likely (conservative growth rate estimates) and optimistic (mid range growth rate estimates) scenarios were employed for arriving at the forecasts which are presented in constant 1980 U.S. dollars. The worldwide satellite market demand forecast predicts that the market between 181 and 2000 will range from $35 to $50 billion. Approximately one-half of the world market, $16 to $20 billion, will be generated in the United States.

Decision Support on the Sediments Flushing of Aimorés Dam Using Medium-Range Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Mainardi Fan, Fernando; Schwanenberg, Dirk; Collischonn, Walter; Assis dos Reis, Alberto; Alvarado Montero, Rodolfo; Alencar Siqueira, Vinicius

2015-04-01

In the present study we investigate the use of medium-range streamflow forecasts in the Doce River basin (Brazil), at the reservoir of Aimorés Hydro Power Plant (HPP). During daily operations this reservoir acts as a "trap" to the sediments that originate from the upstream basin of the Doce River. This motivates a cleaning process called "pass through" to periodically remove the sediments from the reservoir. The "pass through" or "sediments flushing" process consists of a decrease of the reservoir's water level to a certain flushing level when a determined reservoir inflow threshold is forecasted. Then, the water in the approaching inflow is used to flush the sediments from the reservoir through the spillway and to recover the original reservoir storage. To be triggered, the sediments flushing operation requires an inflow larger than 3000m³/s in a forecast horizon of 7 days. This lead-time of 7 days is far beyond the basin's concentration time (around 2 days), meaning that the forecasts for the pass through procedure highly depends on Numerical Weather Predictions (NWP) models that generate Quantitative Precipitation Forecasts (QPF). This dependency creates an environment with a high amount of uncertainty to the operator. To support the decision making at Aimorés HPP we developed a fully operational hydrological forecasting system to the basin. The system is capable of generating ensemble streamflow forecasts scenarios when driven by QPF data from meteorological Ensemble Prediction Systems (EPS). This approach allows accounting for uncertainties in the NWP at a decision making level. This system is starting to be used operationally by CEMIG and is the one shown in the present study, including a hindcasting analysis to assess the performance of the system for the specific flushing problem. The QPF data used in the hindcasting study was derived from the TIGGE (THORPEX Interactive Grand Global Ensemble) database. Among all EPS available on TIGGE, three were selected: ECMWF, GEFS, and CPTEC. As a deterministic reference forecast, we adopt the high resolution ECMWF forecast for comparison. The experiment consisted on running retrospective forecasts for a full five-year period. To verify the proposed objectives of the study, we use different metrics to evaluate the forecast: ROC Curves, Exceedance Diagrams, Forecast Convergence Score (FCS). Metrics results enabled to understand the benefits of the hydrological ensemble prediction system as a decision making tool for the HPP operation. The ROC scores indicate that the use of the lower percentiles of the ensemble scenarios issues for a true alarm rate around 0,5 to 0,8 (depending on the model and on the percentile), for the lead time of seven days. While the false alarm rate is between 0 and 0,3. Those rates were better than the ones resulting from the deterministic reference forecast. Exceedance diagrams and forecast convergence scores indicate that the ensemble scenarios provide an early signal about the threshold crossing. Furthermore, the ensemble forecasts are more consistent between two subsequent forecasts in comparison to the deterministic forecast. The assessments results also give more credibility to CEMIG in the realization and communication of flushing operation with the stakeholders involved.

Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model

PubMed Central

Zhang, Jinlun

2015-01-01

Abstract Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h–8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high‐resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24–48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast. PMID:27818852

A system for forecasting and monitoring cash flow : phase I : forecasting payments on construction contracts.

DOT National Transportation Integrated Search

1983-01-01

The research on which this paper is based was performed as part of a study to develop a system for generating a one-to-two year forecast of monthly cash flows for the Virginia Department of Highways and Transportation. It revealed that presently used...

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

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

Haupt, Sue Ellen

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solarmore » power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.« less

Coastal and Riverine Flood Forecast Model powered by ADCIRC

NASA Astrophysics Data System (ADS)

Khalid, A.; Ferreira, C.

2017-12-01

Coastal flooding is becoming a major threat to increased population in the coastal areas. To protect coastal communities from tropical storms & hurricane damages, early warning systems are being developed. These systems have the capability of real time flood forecasting to identify hazardous coastal areas and aid coastal communities in rescue operations. State of the art hydrodynamic models forced by atmospheric forcing have given modelers the ability to forecast storm surge, water levels and currents. This helps to identify the areas threatened by intense storms. Study on Chesapeake Bay area has gained national importance because of its combined riverine and coastal phenomenon, which leads to greater uncertainty in flood predictions. This study presents an automated flood forecast system developed by following Advanced Circulation (ADCIRC) Surge Guidance System (ASGS) guidelines and tailored to take in riverine and coastal boundary forcing, thus includes all the hydrodynamic processes to forecast total water in the Potomac River. As studies on tidal and riverine flow interaction are very scarce in number, our forecast system would be a scientific tool to examine such area and fill the gaps with precise prediction for Potomac River. Real-time observations from National Oceanic and Atmospheric Administration (NOAA) and field measurements have been used as model boundary feeding. The model performance has been validated by using major historical riverine and coastal flooding events. Hydrodynamic model ADCIRC produced promising predictions for flood inundation areas. As better forecasts can be achieved by using coupled models, this system is developed to take boundary conditions from Global WaveWatchIII for the research purposes. Wave and swell propagation will be fed through Global WavewatchIII model to take into account the effects of swells and currents. This automated forecast system is currently undergoing rigorous testing to include any missing parameters which might provide better and more reliable forecast for the flood affected communities.

Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

NASA Astrophysics Data System (ADS)

Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

2016-12-01

The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Stand Up and Be Counted: The Continuing Challenge of Building the Iraqi Security Forces

DTIC Science & Technology

2007-01-01

forces in conjunction with neutralizing Iraq’s insurgency and developing Iraqi forces capable of securing the country . From the fall of 2003...effort to develop the Iraqi Security Forces (ISF), we cannot assess the operational capability of these forces. We are actually left with more...First we trained the army for threats from outside the country . But we realized the true threats were inside the country …. It’s the Iraqis

Seed-competent HMW tau species accumulates in the cerebrospinal fluid of Alzheimer's disease mouse model and human patients

PubMed Central

Takeda, Shuko; Commins, Caitlin; DeVos, Sarah L.; Nobuhara, Chloe K.; Wegmann, Susanne; Roe, Allyson D.; Costantino, Isabel; Fan, Zhanyun; Nicholls, Samantha B.; Sherman, Alexis E.; Trisini Lipsanopoulos, Ana T.; Scherzer, Clemens R.; Carlson, George A.; Pitstick, Rose; Peskind, Elaine R.; Raskind, Murray A.; Li, Ge; Montine, Thomas J.; Frosch, Matthew P.; Hyman, Bradley T.

2016-01-01

Objective Cerebrospinal fluid (CSF) tau is an excellent surrogate marker for assessing neuropathological changes that occur in Alzheimer's disease (AD) patients. However, whether the elevated tau in AD CSF is just a marker of neurodegeneration or in fact a part of the disease process is uncertain. Moreover, it is unknown how CSF tau relates to the recently described soluble high-molecular-weight (HMW) species that is found in postmortem AD brain and can be taken up by neurons and seed aggregates. Methods We have examined seeding and uptake properties of brain extracellular tau from various sources including: interstitial fluid (ISF) and CSF from an AD transgenic mouse model, and postmortem ventricular and antemortem lumbar CSF from AD patients. Results We found that brain ISF and CSF tau from the AD mouse model can be taken up by cells and induce intracellular aggregates. Ventricular CSF from AD patients contained a rare HMW tau species that exerted a higher seeding activity. Notably, the HMW tau species was also detected in lumbar CSF from AD patients and its levels were significantly elevated compared with control subjects. HMW tau derived from CSF of AD patients was seed-competent in vitro. Interpretation These findings suggest that CSF from an AD brain contains potentially bioactive HMW tau species giving new insights into the role of CSF tau and biomarker development for AD. PMID:27351289

Experimenting with Different Bulking Agents in an Aerobic Food Waste Composter

NASA Astrophysics Data System (ADS)

Chann, S.

2016-12-01

With one third of Hong Kong's solid wastage being food scraps, reducing food waste has become crucial. The ISF Academy, a Hong Kong private school, had an A900 Rocket Food Composter installed in 2013, hoping to reduce its carbon footprint. The 27 metric tons of food wastage produced annually by the school is put through an aerobic process and the wastage is converted into humus. The composter has a capacity of 1750 litres of food and it produces humus every 14 days. The base of the humus consists of a bulking agent and food waste (2:1). A bulking agent is a carbon based material used to absorb moisture and odors, add structure and air and eliminate bugs from humus. This study contains comparative data on a few of the listed bulking agents: Hemp, Kenaf, rapeseed oil straw, miscanthus and shredded cardboard. The aim of this study is to determine an alternative reliable, affordable and suitable bulking agent to wood shavings: the current agent used. The humus produced must pass regulations for "general agricultural use" as it is used for experiential learning and gardening with primary school students. Over 500 children are participating in the school's plantation project, producing legumes for the school cafeteria. ISF pioneers and sets an example for other Hong Kong schools, showing that a composting and plantation scheme, not only proves to have environmental benefits but also educational uses.

Genetic and environmental influences on early literacy skills across school grade contexts.

PubMed

Haughbrook, Rasheda; Hart, Sara A; Schatschneider, Christopher; Taylor, Jeanette

2017-09-01

Recent research suggests that the etiology of reading achievement can differ across environmental contexts. In the US, schools are commonly assigned grades (e.g. 'A', 'B') often interpreted to indicate school quality. This study explored differences in the etiology of early literacy skills for students based on these school grades. Participants included twins drawn from the Florida Twin Project on Reading (n = 1313 pairs) aged 4 to 10 years during the 2006-07 school year. Early literacy skills were assessed with DIBELS subtests: Oral Reading Fluency (ORF), Nonsense Word Fluency (NWF), Initial Sound Fluency (ISF), Letter Naming Fluency (LNF), and Phoneme Segmentation Fluency (PSF). School grade data were retrieved from the Florida Department of Education. Multi-group analyses were conducted separately for subsamples defined by 'A' or 'non-A' schools, controlling for school-level socioeconomic status. Results indicated significant etiological differences on pre-reading skills (ISF, LNF, and PSF), but not word-level reading skills (ORF and NWF). There was a consistent trend of greater environmental influences on pre-reading skills in non-A schools, arguably representing 'poorer' environmental contexts than the A schools. Importantly, this is the case outside of resources linked with school-level SES, indicating that something about the direct environment on pre-reading skills in the non-A school context is more variable than for A schools. © 2016 John Wiley & Sons Ltd.

Impact of design and operation variables on the performance of vertical-flow constructed wetlands and intermittent sand filters treating pond effluent.

PubMed

Torrens, Antonina; Molle, Pascal; Boutin, Catherine; Salgot, Miquel

2009-04-01

With the aim of improving the quality of the effluent from a waste stabilization pond (WSP) different types of vertical-flow constructed wetlands (VFCWs) and intermittent sand filters (ISFs) were tested at a pilot plant in Aurignac (France). The effectiveness of each design at upgrading the pond effluent was studied over a period of 2 years. Physicochemical parameters were monitored by taking composite samples over 24h and grab samples every week. The hydraulic behaviour of the filters was studied using (NaCl) tracer tests and monitoring the infiltration rate. This paper describes the influence on the performance of the beds of: (a) the characteristics of the medium (type of sand, depth, and presence of Phragmites); (b) feed modes; and (c) the presence of an algae clogging layer. The study demonstrates the viability of VFCWs and ISFs as means of upgrading effluent from WSPs. For hydraulic loads (HL) of up to 80cm/day, both technologies effectively retain algae, complete organic matter degradation, and nitrify the pond effluent. The presence of plants did not significantly affect the performance of the filters although it was important in terms of maintenance. The deeper filters presented better removals for all the parameter tested, due to higher hydraulic detention times (HDTs). The dosing regime and resting period duration all affected the hydraulic performance and purification efficiency of the filters.

Suppression of glymphatic fluid transport in a mouse model of Alzheimer's disease.

PubMed

Peng, Weiguo; Achariyar, Thiyagarajan M; Li, Baoman; Liao, Yonghong; Mestre, Humberto; Hitomi, Emi; Regan, Sean; Kasper, Tristan; Peng, Sisi; Ding, Fengfei; Benveniste, Helene; Nedergaard, Maiken; Deane, Rashid

2016-09-01

Glymphatic transport, defined as cerebrospinal fluid (CSF) peri-arterial inflow into brain, and interstitial fluid (ISF) clearance, is reduced in the aging brain. However, it is unclear whether glymphatic transport affects the distribution of soluble Aβ in Alzheimer's disease (AD). In wild type mice, we show that Aβ40 (fluorescently labeled Aβ40 or unlabeled Aβ40), was distributed from CSF to brain, via the peri-arterial space, and associated with neurons. In contrast, Aβ42 was mostly restricted to the peri-arterial space due mainly to its greater propensity to oligomerize when compared to Aβ40. Interestingly, pretreatment with Aβ40 in the CSF, but not Aβ42, reduced CSF transport into brain. In APP/PS1 mice, a model of AD, with and without extensive amyloid-β deposits, glymphatic transport was reduced, due to the accumulation of toxic Aβ species, such as soluble oligomers. CSF-derived Aβ40 co-localizes with existing endogenous vascular and parenchymal amyloid-β plaques, and thus, may contribute to the progression of both cerebral amyloid angiopathy and parenchymal Aβ accumulation. Importantly, glymphatic failure preceded significant amyloid-β deposits, and thus, may be an early biomarker of AD. By extension, restoring glymphatic inflow and ISF clearance are potential therapeutic targets to slow the onset and progression of AD. Copyright © 2016 Elsevier Inc. All rights reserved.

Regional Air Quality forecAST (RAQAST) Over the U.S

NASA Astrophysics Data System (ADS)

Yoshida, Y.; Choi, Y.; Zeng, T.; Wang, Y.

2005-12-01

A regional chemistry and transport modeling system is used to provide 48-hour forecast of the concentrations of ozone and its precursors over the United States. Meteorological forecast is conducted using the NCAR/Penn State MM5 model. The regional chemistry and transport model simulates the sources, transport, chemistry, and deposition of 24 chemical tracers. The lateral and upper boundary conditions of trace gas concentrations are specified using the monthly mean output from the global GEOS-CHEM model. The initial and boundary conditions for meteorological fields are taken from the NOAA AVN forecast. The forecast has been operational since August, 2003. Model simulations are evaluated using surface, aircraft, and satellite measurements in the A'hindcast' mode. The next step is an automated forecast evaluation system.

A Scheme for Short-Term Prediction of Hydrometeors Using Advection and Physical Forcing.

DTIC Science & Technology

1984-07-01

D.A. Lowry, 1978: Use of a real - time computer graphics system for diagnosis and forecasting . Preprints, Conf. on Wes. Forecasting and Analysis and...28 Figure 4.2.1. Graph for forecasting the night minimum temperature from observations at 1800-2000 local time . From Zverev (1972...3u 1. 2 much weather is produced by organized systems that translate, and forecast gains were made through use of the concepts of steering

An experimental system for flood risk forecasting at global scale

NASA Astrophysics Data System (ADS)

Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

2016-12-01

Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

iFLOOD: A Real Time Flood Forecast System for Total Water Modeling in the National Capital Region

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Ferreira, C.

2017-12-01

Extreme flood events are the costliest natural hazards impacting the US and frequently cause extensive damages to infrastructure, disruption to economy and loss of lives. In 2016, Hurricane Matthew brought severe damage to South Carolina and demonstrated the importance of accurate flood hazard predictions that requires the integration of riverine and coastal model forecasts for total water prediction in coastal and tidal areas. The National Weather Service (NWS) and the National Ocean Service (NOS) provide flood forecasts for almost the entire US, still there are service-gap areas in tidal regions where no official flood forecast is available. The National capital region is vulnerable to multi-flood hazards including high flows from annual inland precipitation events and surge driven coastal inundation along the tidal Potomac River. Predicting flood levels on such tidal areas in river-estuarine zone is extremely challenging. The main objective of this study is to develop the next generation of flood forecast systems capable of providing accurate and timely information to support emergency management and response in areas impacted by multi-flood hazards. This forecast system is capable of simulating flood levels in the Potomac and Anacostia River incorporating the effects of riverine flooding from the upstream basins, urban storm water and tidal oscillations from the Chesapeake Bay. Flood forecast models developed so far have been using riverine data to simulate water levels for Potomac River. Therefore, the idea is to use forecasted storm surge data from a coastal model as boundary condition of this system. Final output of this validated model will capture the water behavior in river-estuary transition zone far better than the one with riverine data only. The challenge for this iFLOOD forecast system is to understand the complex dynamics of multi-flood hazards caused by storm surges, riverine flow, tidal oscillation and urban storm water. Automated system simulations will help to develop a seamless integration with the boundary systems in the service-gap area with new insights into our scientific understanding of such complex systems. A visualization system is being developed to allow stake holders and the community to have access to the flood forecasting for their region with sufficient lead time.

Operational Earthquake Forecasting of Aftershocks for New England

NASA Astrophysics Data System (ADS)

Ebel, J.; Fadugba, O. I.

2015-12-01

Although the forecasting of mainshocks is not possible, recent research demonstrates that probabilistic forecasts of expected aftershock activity following moderate and strong earthquakes is possible. Previous work has shown that aftershock sequences in intraplate regions behave similarly to those in California, and thus the operational aftershocks forecasting methods that are currently employed in California can be adopted for use in areas of the eastern U.S. such as New England. In our application, immediately after a felt earthquake in New England, a forecast of expected aftershock activity for the next 7 days will be generated based on a generic aftershock activity model. Approximately 24 hours after the mainshock, the parameters of the aftershock model will be updated using the observed aftershock activity observed to that point in time, and a new forecast of expected aftershock activity for the next 7 days will be issued. The forecast will estimate the average number of weak, felt aftershocks and the average expected number of aftershocks based on the aftershock statistics of past New England earthquakes. The forecast also will estimate the probability that an earthquake that is stronger than the mainshock will take place during the next 7 days. The aftershock forecast will specify the expected aftershocks locations as well as the areas over which aftershocks of different magnitudes could be felt. The system will use web pages, email and text messages to distribute the aftershock forecasts. For protracted aftershock sequences, new forecasts will be issued on a regular basis, such as weekly. Initially, the distribution system of the aftershock forecasts will be limited, but later it will be expanded as experience with and confidence in the system grows.

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

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

Freedman, Jeffrey M.; Manobianco, John; Schroeder, John

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10more » - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.« less

Constraints on Rational Model Weighting, Blending and Selecting when Constructing Probability Forecasts given Multiple Models

NASA Astrophysics Data System (ADS)

Higgins, S. M. W.; Du, H. L.; Smith, L. A.

2012-04-01

Ensemble forecasting on a lead time of seconds over several years generates a large forecast-outcome archive, which can be used to evaluate and weight "models". Challenges which arise as the archive becomes smaller are investigated: in weather forecasting one typically has only thousands of forecasts however those launched 6 hours apart are not independent of each other, nor is it justified to mix seasons with different dynamics. Seasonal forecasts, as from ENSEMBLES and DEMETER, typically have less than 64 unique launch dates; decadal forecasts less than eight, and long range climate forecasts arguably none. It is argued that one does not weight "models" so much as entire ensemble prediction systems (EPSs), and that the marginal value of an EPS will depend on the other members in the mix. The impact of using different skill scores is examined in the limits of both very large forecast-outcome archives (thereby evaluating the efficiency of the skill score) and in very small forecast-outcome archives (illustrating fundamental limitations due to sampling fluctuations and memory in the physical system being forecast). It is shown that blending with climatology (J. Bröcker and L.A. Smith, Tellus A, 60(4), 663-678, (2008)) tends to increase the robustness of the results; also a new kernel dressing methodology (simply insuring that the expected probability mass tends to lie outside the range of the ensemble) is illustrated. Fair comparisons using seasonal forecasts from the ENSEMBLES project are used to illustrate the importance of these results with fairly small archives. The robustness of these results across the range of small, moderate and huge archives is demonstrated using imperfect models of perfectly known nonlinear (chaotic) dynamical systems. The implications these results hold for distinguishing the skill of a forecast from its value to a user of the forecast are discussed.

Validation of Seasonal Forecast of Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Das, Sukanta Kumar; Deb, Sanjib Kumar; Kishtawal, C. M.; Pal, Pradip Kumar

2015-06-01

The experimental seasonal forecast of Indian summer monsoon (ISM) rainfall during June through September using Community Atmosphere Model (CAM) version 3 has been carried out at the Space Applications Centre Ahmedabad since 2009. The forecasts, based on a number of ensemble members (ten minimum) of CAM, are generated in several phases and updated on regular basis. On completion of 5 years of experimental seasonal forecasts in operational mode, it is required that the overall validation or correctness of the forecast system is quantified and that the scope is assessed for further improvements of the forecast over time, if any. The ensemble model climatology generated by a set of 20 identical CAM simulations is considered as the model control simulation. The performance of the forecast has been evaluated by assuming the control simulation as the model reference. The forecast improvement factor shows positive improvements, with higher values for the recent forecasted years as compared to the control experiment over the Indian landmass. The Taylor diagram representation of the Pearson correlation coefficient (PCC), standard deviation and centered root mean square difference has been used to demonstrate the best PCC, in the order of 0.74-0.79, recorded for the seasonal forecast made during 2013. Further, the bias score of different phases of experiment revealed the fact that the ISM rainfall forecast is affected by overestimation in predicting the low rain-rate (less than 7 mm/day), but by underestimation in the medium and high rain-rate (higher than 11 mm/day). Overall, the analysis shows significant improvement of the ISM forecast over the last 5 years, viz. 2009-2013, due to several important modifications that have been implemented in the forecast system. The validation exercise has also pointed out a number of shortcomings in the forecast system; these will be addressed in the upcoming years of experiments to improve the quality of the ISM prediction.

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

NASA Technical Reports Server (NTRS)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

2017-06-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

The FireWork air quality forecast system with near-real-time biomass burning emissions: Recent developments and evaluation of performance for the 2015 North American wildfire season

PubMed Central

Pavlovic, Radenko; Chen, Jack; Anderson, Kerry; Moran, Michael D.; Beaulieu, Paul-André; Davignon, Didier; Cousineau, Sophie

2016-01-01

ABSTRACT Environment and Climate Change Canada’s FireWork air quality (AQ) forecast system for North America with near-real-time biomass burning emissions has been running experimentally during the Canadian wildfire season since 2013. The system runs twice per day with model initializations at 00 UTC and 12 UTC, and produces numerical AQ forecast guidance with 48-hr lead time. In this work we describe the FireWork system, which incorporates near-real-time biomass burning emissions based on the Canadian Wildland Fire Information System (CWFIS) as an input to the operational Regional Air Quality Deterministic Prediction System (RAQDPS). To demonstrate the capability of the system we analyzed two forecast periods in 2015 (June 2–July 15, and August 15–31) when fire activity was high, and observed fire-smoke-impacted areas in western Canada and the western United States. Modeled PM2.5 surface concentrations were compared with surface measurements and benchmarked with results from the operational RAQDPS, which did not consider near-real-time biomass burning emissions. Model performance statistics showed that FireWork outperformed RAQDPS with improvements in forecast hourly PM2.5 across the region; the results were especially significant for stations near the path of fire plume trajectories. Although the hourly PM2.5 concentrations predicted by FireWork still displayed bias for areas with active fires for these two periods (mean bias [MB] of –7.3 µg m−3 and 3.1 µg m−3), it showed better forecast skill than the RAQDPS (MB of –11.7 µg m−3 and –5.8 µg m−3) and demonstrated a greater ability to capture temporal variability of episodic PM2.5 events (correlation coefficient values of 0.50 and 0.69 for FireWork compared to 0.03 and 0.11 for RAQDPS). A categorical forecast comparison based on an hourly PM2.5 threshold of 30 µg m−3 also showed improved scores for probability of detection (POD), critical success index (CSI), and false alarm rate (FAR). Implications: Smoke from wildfires can have a large impact on regional air quality (AQ) and can expose populations to elevated pollution levels. Environment and Climate Change Canada has been producing operational air quality forecasts for all of Canada since 2009 and is now working to include near-real-time wildfire emissions (NRTWE) in its operational AQ forecasting system. An experimental forecast system named FireWork, which includes NRTWE, has been undergoing testing and evaluation since 2013. A performance analysis of FireWork forecasts for the 2015 wildfire season shows that FireWork provides significant improvements to surface PM2.5 forecasts and valuable guidance to regional forecasters and first responders. PMID:26934496

Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks

PubMed Central

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway. PMID:25544838

Benchmark analysis of forecasted seasonal temperature over different climatic areas

NASA Astrophysics Data System (ADS)

Giunta, G.; Salerno, R.; Ceppi, A.; Ercolani, G.; Mancini, M.

2015-12-01

From a long-term perspective, an improvement of seasonal forecasting, which is often exclusively based on climatology, could provide a new capability for the management of energy resources in a time scale of just a few months. This paper regards a benchmark analysis in relation to long-term temperature forecasts over Italy in the year 2010, comparing the eni-kassandra meteo forecast (e-kmf®) model, the Climate Forecast System-National Centers for Environmental Prediction (CFS-NCEP) model, and the climatological reference (based on 25-year data) with observations. Statistical indexes are used to understand the reliability of the prediction of 2-m monthly air temperatures with a perspective of 12 weeks ahead. The results show how the best performance is achieved by the e-kmf® system which improves the reliability for long-term forecasts compared to climatology and the CFS-NCEP model. By using the reliable high-performance forecast system, it is possible to optimize the natural gas portfolio and management operations, thereby obtaining a competitive advantage in the European energy market.

Environmental noise forecasting based on support vector machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

2018-01-01

As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

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

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-08-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

Climatological Observations for Maritime Prediction and Analysis Support Service (COMPASS)

NASA Astrophysics Data System (ADS)

OConnor, A.; Kirtman, B. P.; Harrison, S.; Gorman, J.

2016-02-01

Current US Navy forecasting systems cannot easily incorporate extended-range forecasts that can improve mission readiness and effectiveness; ensure safety; and reduce cost, labor, and resource requirements. If Navy operational planners had systems that incorporated these forecasts, they could plan missions using more reliable and longer-term weather and climate predictions. Further, using multi-model forecast ensembles instead of single forecasts would produce higher predictive performance. Extended-range multi-model forecast ensembles, such as those available in the North American Multi-Model Ensemble (NMME), are ideal for system integration because of their high skill predictions; however, even higher skill predictions can be produced if forecast model ensembles are combined correctly. While many methods for weighting models exist, the best method in a given environment requires expert knowledge of the models and combination methods.We present an innovative approach that uses machine learning to combine extended-range predictions from multi-model forecast ensembles and generate a probabilistic forecast for any region of the globe up to 12 months in advance. Our machine-learning approach uses 30 years of hindcast predictions to learn patterns of forecast model successes and failures. Each model is assigned a weight for each environmental condition, 100 km2 region, and day given any expected environmental information. These weights are then applied to the respective predictions for the region and time of interest to effectively stitch together a single, coherent probabilistic forecast. Our experimental results demonstrate the benefits of our approach to produce extended-range probabilistic forecasts for regions and time periods of interest that are superior, in terms of skill, to individual NMME forecast models and commonly weighted models. The probabilistic forecast leverages the strengths of three NMME forecast models to predict environmental conditions for an area spanning from San Diego, CA to Honolulu, HI, seven months in-advance. Key findings include: weighted combinations of models are strictly better than individual models; machine-learned combinations are especially better; and forecasts produced using our approach have the highest rank probability skill score most often.

Utility of flood warning systems for emergency management

NASA Astrophysics Data System (ADS)

Molinari, Daniela; Ballio, Francesco; Menoni, Scira

2010-05-01

The presentation is focused on a simple and crucial question for warning systems: are flood and hydrological modelling and forecasting helpful to manage flood events? Indeed, it is well known that a warning process can be invalidated by inadequate forecasts so that the accuracy and robustness of the previsional model is a key issue for any flood warning procedure. However, one problem still arises at this perspective: when forecasts can be considered to be adequate? According to Murphy (1993, Wea. Forecasting 8, 281-293), forecasts hold no intrinsic value but they acquire it through their ability to influence the decisions made by their users. Moreover, we can add that forecasts value depends on the particular problem at stake showing, this way, a multifaceted nature. As a result, forecasts verification should not be seen as a universal process, instead it should be tailored to the particular context in which forecasts are implemented. This presentation focuses on warning problems in mountain regions, whereas the short time which is distinctive of flood events makes the provision of adequate forecasts particularly significant. In this context, the quality of a forecast is linked to its capability to reduce the impact of a flood by improving the correctness of the decision about issuing (or not) a warning as well as of the implementation of a proper set of actions aimed at lowering potential flood damages. The present study evaluates the performance of a real flood forecasting system from this perspective. In detail, a back analysis of past flood events and available verification tools have been implemented. The final objective was to evaluate the system ability to support appropriate decisions with respect not only to the flood characteristics but also to the peculiarities of the area at risk as well as to the uncertainty of forecasts. This meant to consider also flood damages and forecasting uncertainty among the decision variables. Last but not least, the presentation explains how the procedure implemented in the case study could support the definition of a proper warning rule.

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

PubMed

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Valuing year-to-go hydrologic forecast improvements for a peaking hydropower system in the Sierra Nevada

NASA Astrophysics Data System (ADS)

Rheinheimer, David E.; Bales, Roger C.; Oroza, Carlos A.; Lund, Jay R.; Viers, Joshua H.

2016-05-01

We assessed the potential value of hydrologic forecasting improvements for a snow-dominated high-elevation hydropower system in the Sierra Nevada of California, using a hydropower optimization model. To mimic different forecasting skill levels for inflow time series, rest-of-year inflows from regression-based forecasts were blended in different proportions with representative inflows from a spatially distributed hydrologic model. The statistical approach mimics the simpler, historical forecasting approach that is still widely used. Revenue was calculated using historical electricity prices, with perfect price foresight assumed. With current infrastructure and operations, perfect hydrologic forecasts increased annual hydropower revenue by 0.14 to 1.6 million, with lower values in dry years and higher values in wet years, or about $0.8 million (1.2%) on average, representing overall willingness-to-pay for perfect information. A second sensitivity analysis found a wider range of annual revenue gain or loss using different skill levels in snow measurement in the regression-based forecast, mimicking expected declines in skill as the climate warms and historical snow measurements no longer represent current conditions. The value of perfect forecasts was insensitive to storage capacity for small and large reservoirs, relative to average inflow, and modestly sensitive to storage capacity with medium (current) reservoir storage. The value of forecasts was highly sensitive to powerhouse capacity, particularly for the range of capacities in the northern Sierra Nevada. The approach can be extended to multireservoir, multipurpose systems to help guide investments in forecasting.

Moisture Forecast Bias Correction in GEOS DAS

NASA Technical Reports Server (NTRS)

Dee, D.

1999-01-01

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

Econometric Models for Forecasting of Macroeconomic Indices

ERIC Educational Resources Information Center

Sukhanova, Elena I.; Shirnaeva, Svetlana Y.; Mokronosov, Aleksandr G.

2016-01-01

The urgency of the research topic was stipulated by the necessity to carry out an effective controlled process by the economic system which can hardly be imagined without indices forecasting characteristic of this system. An econometric model is a safe tool of forecasting which makes it possible to take into consideration the trend of indices…

Load Modeling and Forecasting | Grid Modernization | NREL

Science.gov Websites

Load Modeling and Forecasting Load Modeling and Forecasting NREL's work in load modeling is focused resources (such as rooftop photovoltaic systems) and changing customer energy use profiles, new load models distribution system. In addition, NREL researchers are developing load models for individual appliances and

Global Ocean Forecast System (GOFS) Version 2.6. User’s Manual

DTIC Science & Technology

2010-03-31

odimens.D, which takes the rivers.dat flow levels, inputs an SST and sea surface salinity (SSS) climatology from GDEM , and outputs the orivs_1.D...Center for Medium-range Weather Forecast GB GigaByte GDEM Global Digital Elevation Map GOFS Global Ocean Forecast System HPCMP High Performance

Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation

NASA Astrophysics Data System (ADS)

Benedetti, A.; Morcrette, J.-J.; Boucher, O.; Dethof, A.; Engelen, R. J.; Fisher, M.; Flentje, H.; Huneeus, N.; Jones, L.; Kaiser, J. W.; Kinne, S.; Mangold, A.; Razinger, M.; Simmons, A. J.; Suttie, M.

2009-07-01

This study presents the new aerosol assimilation system, developed at the European Centre for Medium-Range Weather Forecasts, for the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) project. The aerosol modeling and analysis system is fully integrated in the operational four-dimensional assimilation apparatus. Its purpose is to produce aerosol forecasts and reanalyses of aerosol fields using optical depth data from satellite sensors. This paper is the second of a series which describes the GEMS aerosol effort. It focuses on the theoretical architecture and practical implementation of the aerosol assimilation system. It also provides a discussion of the background errors and observations errors for the aerosol fields, and presents a subset of results from the 2-year reanalysis which has been run for 2003 and 2004 using data from the Moderate Resolution Imaging Spectroradiometer on the Aqua and Terra satellites. Independent data sets are used to show that despite some compromises that have been made for feasibility reasons in regards to the choice of control variable and error characteristics, the analysis is very skillful in drawing to the observations and in improving the forecasts of aerosol optical depth.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

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

Jiang, Huaiguang

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.« less

Research on Nonlinear Time Series Forecasting of Time-Delay NN Embedded with Bayesian Regularization

NASA Astrophysics Data System (ADS)

Jiang, Weijin; Xu, Yusheng; Xu, Yuhui; Wang, Jianmin

Based on the idea of nonlinear prediction of phase space reconstruction, this paper presented a time delay BP neural network model, whose generalization capability was improved by Bayesian regularization. Furthermore, the model is applied to forecast the imp&exp trades in one industry. The results showed that the improved model has excellent generalization capabilities, which not only learned the historical curve, but efficiently predicted the trend of business. Comparing with common evaluation of forecasts, we put on a conclusion that nonlinear forecast can not only focus on data combination and precision improvement, it also can vividly reflect the nonlinear characteristic of the forecasting system. While analyzing the forecasting precision of the model, we give a model judgment by calculating the nonlinear characteristic value of the combined serial and original serial, proved that the forecasting model can reasonably 'catch' the dynamic characteristic of the nonlinear system which produced the origin serial.

Impact of scatterometer wind (ASCAT-A/B) data assimilation on semi real-time forecast system at KIAPS

NASA Astrophysics Data System (ADS)

Han, H. J.; Kang, J. H.

2016-12-01

Since Jul. 2015, KIAPS (Korea Institute of Atmospheric Prediction Systems) has been performing the semi real-time forecast system to assess the performance of their forecast system as a NWP model. KPOP (KIAPS Protocol for Observation Processing) is a part of KIAPS data assimilation system and has been performing well in KIAPS semi real-time forecast system. In this study, due to the fact that KPOP would be able to treat the scatterometer wind data, we analyze the effect of scatterometer wind (ASCAT-A/B) on KIAPS semi real-time forecast system. O-B global distribution and statistics of scatterometer wind give use two information which are the difference between background field and observation is not too large and KPOP processed the scatterometer wind data well. The changes of analysis increment because of O-B global distribution appear remarkably at the bottom of atmospheric field. It also shows that scatterometer wind data cover wide ocean where data would be able to short. Performance of scatterometer wind data can be checked through the vertical error reduction against IFS between background and analysis field and vertical statistics of O-A. By these analysis result, we can notice that scatterometer wind data will influence the positive effect on lower level performance of semi real-time forecast system at KIAPS. After, long-term result based on effect of scatterometer wind data will be analyzed.

Comparing Two Approaches for Assessing Observation Impact

NASA Technical Reports Server (NTRS)

Todling, Ricardo

2013-01-01

Langland and Baker introduced an approach to assess the impact of observations on the forecasts. In that approach, a state-space aspect of the forecast is defined and a procedure is derived ultimately relating changes in the aspect with changes in the observing system. Some features of the state-space approach are to be noted: the typical choice of forecast aspect is rather subjective and leads to incomplete assessment of the observing system, it requires availability of a verification state that is in practice correlated with the forecast, and it involves the adjoint operator of the entire data assimilation system and is thus constrained by the validity of this operator. This article revisits the topic of observation impacts from the perspective of estimation theory. An observation-space metric is used to allow inferring observation impact on the forecasts without the limitations just mentioned. Using differences of observation-minus-forecast residuals obtained from consecutive forecasts leads to the following advantages: (i) it suggests a rather natural choice of forecast aspect that directly links to the data assimilation procedure, (ii) it avoids introducing undesirable correlations in the forecast aspect since verification is done against the observations, and (iii) it does not involve linearization and use of adjoints. The observation-space approach has the additional advantage of being nearly cost free and very simple to implement. In its simplest form it reduces to evaluating the statistics of observationminus- background and observation-minus-analysis residuals with traditional methods. Illustrations comparing the approaches are given using the NASA Goddard Earth Observing System.

Why preferring parametric forecasting to nonparametric methods?

PubMed

Jabot, Franck

2015-05-07

A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, N. C.; Errico, Ronald M.

2015-01-01

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

Science and Engineering of an Operational Tsunami Forecasting System

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

Gonzalez, Frank

2009-04-06

After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

Science and Engineering of an Operational Tsunami Forecasting System

ScienceCinema

Gonzalez, Frank

2017-12-09

After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology

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

Hamann, Hendrik F.

The goal of the project was the development and demonstration of a significantly improved solar forecasting technology (short: Watt-sun), which leverages new big data processing technologies and machine-learnt blending between different models and forecast systems. The technology aimed demonstrating major advances in accuracy as measured by existing and new metrics which themselves were developed as part of this project. Finally, the team worked with Independent System Operators (ISOs) and utilities to integrate the forecasts into their operations.

Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS)

DTIC Science & Technology

2016-09-01

Laboratory Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS) by JL Cogan...analysis. As expected, accuracy generally tended to decline as the large-scale data aged , but appeared to improve slightly as the age of the large...19 Table 7 Minimum and maximum mean RMDs for each WRF time (or GFS data age ) category. Minimum and

Evaluations of Extended-Range tropical Cyclone Forecasts in the Western North Pacific by using the Ensemble Reforecasts: Preliminary Results

NASA Astrophysics Data System (ADS)

Tsai, Hsiao-Chung; Chen, Pang-Cheng; Elsberry, Russell L.

2017-04-01

The objective of this study is to evaluate the predictability of the extended-range forecasts of tropical cyclone (TC) in the western North Pacific using reforecasts from National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) during 1996-2015, and from the Climate Forecast System (CFS) during 1999-2010. Tsai and Elsberry have demonstrated that an opportunity exists to support hydrological operations by using the extended-range TC formation and track forecasts in the western North Pacific from the ECMWF 32-day ensemble. To demonstrate this potential for the decision-making processes regarding water resource management and hydrological operation in Taiwan reservoir watershed areas, special attention is given to the skill of the NCEP GEFS and CFS models in predicting the TCs affecting the Taiwan area. The first objective of this study is to analyze the skill of NCEP GEFS and CFS TC forecasts and quantify the forecast uncertainties via verifications of categorical binary forecasts and probabilistic forecasts. The second objective is to investigate the relationships among the large-scale environmental factors [e.g., El Niño Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), etc.] and the model forecast errors by using the reforecasts. Preliminary results are indicating that the skill of the TC activity forecasts based on the raw forecasts can be further improved if the model biases are minimized by utilizing these reforecasts.

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

A non-parametric postprocessor for bias-correcting multi-model ensemble forecasts of hydrometeorological and hydrologic variables

NASA Astrophysics Data System (ADS)

Brown, James; Seo, Dong-Jun

2010-05-01

Operational forecasts of hydrometeorological and hydrologic variables often contain large uncertainties, for which ensemble techniques are increasingly used. However, the utility of ensemble forecasts depends on the unbiasedness of the forecast probabilities. We describe a technique for quantifying and removing biases from ensemble forecasts of hydrometeorological and hydrologic variables, intended for use in operational forecasting. The technique makes no a priori assumptions about the distributional form of the variables, which is often unknown or difficult to model parametrically. The aim is to estimate the conditional cumulative distribution function (ccdf) of the observed variable given a (possibly biased) real-time ensemble forecast from one or several forecasting systems (multi-model ensembles). The technique is based on Bayesian optimal linear estimation of indicator variables, and is analogous to indicator cokriging (ICK) in geostatistics. By developing linear estimators for the conditional expectation of the observed variable at many thresholds, ICK provides a discrete approximation of the full ccdf. Since ICK minimizes the conditional error variance of the indicator expectation at each threshold, it effectively minimizes the Continuous Ranked Probability Score (CRPS) when infinitely many thresholds are employed. However, the ensemble members used as predictors in ICK, and other bias-correction techniques, are often highly cross-correlated, both within and between models. Thus, we propose an orthogonal transform of the predictors used in ICK, which is analogous to using their principal components in the linear system of equations. This leads to a well-posed problem in which a minimum number of predictors are used to provide maximum information content in terms of the total variance explained. The technique is used to bias-correct precipitation ensemble forecasts from the NCEP Global Ensemble Forecast System (GEFS), for which independent validation results are presented. Extension to multimodel ensembles from the NCEP GFS and Short Range Ensemble Forecast (SREF) systems is also proposed.

An Operational Short-Term Forecasting System for Regional Hydropower Management

NASA Astrophysics Data System (ADS)

Gronewold, A.; Labuhn, K. A.; Calappi, T. J.; MacNeil, A.

2017-12-01

The Niagara River is the natural outlet of Lake Erie and drains four of the five Great lakes. The river is used to move commerce and is home to both sport fishing and tourism industries. It also provides nearly 5 million kilowatts of hydropower for approximately 3.9 million homes. Due to a complex international treaty and the necessity of balancing water needs for an extensive tourism industry, the power entities operating on the river require detailed and accurate short-term river flow forecasts to maximize power output. A new forecast system is being evaluated that takes advantage of several previously independent components including the NOAA Lake Erie operational Forecast System (LEOFS), a previously developed HEC-RAS model, input from the New York Power Authority(NYPA) and Ontario Power Generation (OPG) and lateral flow forecasts for some of the tributaries provided by the NOAA Northeast River Forecast Center (NERFC). The Corps of Engineers updated the HEC-RAS model of the upper Niagara River to use the output forcing from LEOFS and a planned Grass Island Pool elevation provided by the power entities. The entire system has been integrated at the NERFC; it will be run multiple times per day with results provided to the Niagara River Control Center operators. The new model helps improve discharge forecasts by better accounting for dynamic conditions on Lake Erie. LEOFS captures seiche events on the lake that are often several meters of displacement from still water level. These seiche events translate into flow spikes that HEC-RAS routes downstream. Knowledge of the peak arrival time helps improve operational decisions at the Grass Island Pool. This poster will compare and contrast results from the existing operational flow forecast and the new integrated LEOFS/HEC-RAS forecast. This additional model will supply the Niagara River Control Center operators with multiple forecasts of flow to help improve forecasting under a wider variety of conditions.

Exploring the calibration of a wind forecast ensemble for energy applications

NASA Astrophysics Data System (ADS)

Heppelmann, Tobias; Ben Bouallegue, Zied; Theis, Susanne

2015-04-01

In the German research project EWeLiNE, Deutscher Wetterdienst (DWD) and Fraunhofer Institute for Wind Energy and Energy System Technology (IWES) are collaborating with three German Transmission System Operators (TSO) in order to provide the TSOs with improved probabilistic power forecasts. Probabilistic power forecasts are derived from probabilistic weather forecasts, themselves derived from ensemble prediction systems (EPS). Since the considered raw ensemble wind forecasts suffer from underdispersiveness and bias, calibration methods are developed for the correction of the model bias and the ensemble spread bias. The overall aim is to improve the ensemble forecasts such that the uncertainty of the possible weather deployment is depicted by the ensemble spread from the first forecast hours. Additionally, the ensemble members after calibration should remain physically consistent scenarios. We focus on probabilistic hourly wind forecasts with horizon of 21 h delivered by the convection permitting high-resolution ensemble system COSMO-DE-EPS which has become operational in 2012 at DWD. The ensemble consists of 20 ensemble members driven by four different global models. The model area includes whole Germany and parts of Central Europe with a horizontal resolution of 2.8 km and a vertical resolution of 50 model levels. For verification we use wind mast measurements around 100 m height that corresponds to the hub height of wind energy plants that belong to wind farms within the model area. Calibration of the ensemble forecasts can be performed by different statistical methods applied to the raw ensemble output. Here, we explore local bivariate Ensemble Model Output Statistics at individual sites and quantile regression with different predictors. Applying different methods, we already show an improvement of ensemble wind forecasts from COSMO-DE-EPS for energy applications. In addition, an ensemble copula coupling approach transfers the time-dependencies of the raw ensemble to the calibrated ensemble. The calibrated wind forecasts are evaluated first with univariate probabilistic scores and additionally with diagnostics of wind ramps in order to assess the time-consistency of the calibrated ensemble members.

Assessment of Folsom Lake Watershed response to historical and potential future climate scenarios

USGS Publications Warehouse

Carpenter, Theresa M.; Georgakakos, Konstantine P.

2000-01-01

An integrated forecast-control system was designed to allow the profitable use of ensemble forecasts for the operational management of multi-purpose reservoirs. The system ingests large-scale climate model monthly precipitation through the adjustment of the marginal distribution of reservoir-catchment precipitation to reflect occurrence of monthly climate precipitation amounts in the extreme terciles of their distribution. Generation of ensemble reservoir inflow forecasts is then accomplished with due account for atmospheric- forcing and hydrologic- model uncertainties. These ensemble forecasts are ingested by the decision component of the integrated system, which generates non- inferior trade-off surfaces and, given management preferences, estimates of reservoir- management benefits over given periods. In collaboration with the Bureau of Reclamation and the California Nevada River Forecast Center, the integrated system is applied to Folsom Lake in California to evaluate the benefits for flood control, hydroelectric energy production, and low flow augmentation. In addition to retrospective studies involving the historical period 1964-1993, system simulations were performed for the future period 2001-2030, under a control (constant future greenhouse-gas concentrations assumed at the present levels) and a greenhouse-gas- increase (1-% per annum increase assumed) scenario. The present paper presents and validates ensemble 30-day reservoir- inflow forecasts under a variety of situations. Corresponding reservoir management results are presented in Yao and Georgakakos, A., this issue. Principle conclusions of this paper are that the integrated system provides reliable ensemble inflow volume forecasts at the 5-% confidence level for the majority of the deciles of forecast frequency, and that the use of climate model simulations is beneficial mainly during high flow periods. It is also found that, for future periods with potential sharp climatic increases of precipitation amount and to maintain good reliability levels, operational ensemble inflow forecasting should involve atmospheric forcing from appropriate climatic periods.

Improved Weather Forecasting for the Dynamic Scheduling System of the Green Bank Telescope

NASA Astrophysics Data System (ADS)

Henry, Kari; Maddalena, Ronald

2018-01-01

The Robert C Byrd Green Bank Telescope (GBT) uses a software system that dynamically schedules observations based on models of vertical weather forecasts produced by the National Weather Service (NWS). The NWS provides hourly forecasted values for ~60 layers that extend into the stratosphere over the observatory. We use models, recommended by the Radiocommunication Sector of the International Telecommunications Union, to derive the absorption coefficient in each layer for each hour in the NWS forecasts and for all frequencies over which the GBT has receivers, 0.1 to 115 GHz. We apply radiative transfer models to derive the opacity and the atmospheric contributions to the system temperature, thereby deriving forecasts applicable to scheduling radio observations for up to 10 days into the future. Additionally, the algorithms embedded in the data processing pipeline use historical values of the forecasted opacity to calibrate observations. Until recently, we have concentrated on predictions for high frequency (> 15 GHz) observing, as these need to be scheduled carefully around bad weather. We have been using simple models for the contribution of rain and clouds since we only schedule low-frequency observations under these conditions. In this project, we wanted to improve the scheduling of the GBT and data calibration at low frequencies by deriving better algorithms for clouds and rain. To address the limitation at low frequency, the observatory acquired a Radiometrics Corporation MP-1500A radiometer, which operates in 27 channels between 22 and 30 GHz. By comparing 16 months of measurements from the radiometer against forecasted system temperatures, we have confirmed that forecasted system temperatures are indistinguishable from those measured under good weather conditions. Small miss-calibrations of the radiometer data dominate the comparison. By using recalibrated radiometer measurements, we looked at bad weather days to derive better models for forecasting the contribution of clouds to the opacity and system temperatures. We will show how these revised algorithms should help us improve both data calibration and the accuracy of scheduling low-frequency observations.

Real-time drought forecasting system for irrigation management

NASA Astrophysics Data System (ADS)

Ceppi, A.; Ravazzani, G.; Corbari, C.; Salerno, R.; Meucci, S.; Mancini, M.

2014-09-01

In recent years frequent periods of water scarcity have enhanced the need to use water more carefully, even in European areas which traditionally have an abundant supply of water, such as the Po Valley in northern Italy. In dry periods, water shortage problems can be enhanced by conflicting uses of water, such as irrigation, industry and power production (hydroelectric and thermoelectric). Furthermore, in the last decade the social perspective in relation to this issue has been increasing due to the possible impact of climate change and global warming scenarios which emerge from the IPCC Fifth Assessment Report (IPCC, 2013). Hence, the increased frequency of drought periods has stimulated the improvement of irrigation and water management. In this study we show the development and implementation of the PREGI real-time drought forecasting system; PREGI is an Italian acronym that means "hydro-meteorological forecast for irrigation management". The system, planned as a tool for irrigation optimization, is based on meteorological ensemble forecasts (20 members) at medium range (30 days) coupled with hydrological simulations of water balance to forecast the soil water content on a maize field in the Muzza Bassa Lodigiana (MBL) consortium in northern Italy. The hydrological model was validated against measurements of latent heat flux acquired by an eddy-covariance station, and soil moisture measured by TDR (time domain reflectivity) probes; the reliability of this forecasting system and its benefits were assessed in the 2012 growing season. The results obtained show how the proposed drought forecasting system is able to have a high reliability of forecast at least for 7-10 days ahead of time.

PERFORMANCE AND DIAGNOSTIC EVALUATION OF OZONE PREDICTIONS BY THE ETA-COMMUNITY MULTISCALE AIR QUALITY FORECAST SYSTEM DURING THE 2002 NEW ENGLAND AIR QUALITY STUDY

EPA Science Inventory

A real-time air quality forecasting system (Eta-CMAQ model suite) has been developed by linking the NCEP Eta model to the U.S. EPA CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting O₃ over the northeastern U.S d...

Satellite temperature monitoring and prediction system

NASA Technical Reports Server (NTRS)

Barnett, U. R.; Martsolf, J. D.; Crosby, F. L.

1980-01-01

The paper describes the Florida Satellite Freeze Forecast System (SFFS) in its current state. All data collection options have been demonstrated, and data collected over a three year period have been stored for future analysis. Presently, specific minimum temperature forecasts are issued routinely from November through March. The procedures for issuing these forecast are discussed. The automated data acquisition and processing system is described, and the physical and statistical models employed are examined.

Verification and intercomparison of mesoscale ensemble prediction systems in the Beijing 2008 Olympics Research and Development Project

NASA Astrophysics Data System (ADS)

Kunii, Masaru; Saito, Kazuo; Seko, Hiromu; Hara, Masahiro; Hara, Tabito; Yamaguchi, Munehiko; Gong, Jiandong; Charron, Martin; Du, Jun; Wang, Yong; Chen, Dehui

2011-05-01

During the period around the Beijing 2008 Olympic Games, the Beijing 2008 Olympics Research and Development Project (B08RDP) was conducted as part of the World Weather Research Program short-range weather forecasting research project. Mesoscale ensemble prediction (MEP) experiments were carried out by six organizations in near-real time, in order to share their experiences in the development of MEP systems. The purpose of this study is to objectively verify these experiments and to clarify the problems associated with the current MEP systems through the same experiences. Verification was performed using the MEP outputs interpolated into a common verification domain with a horizontal resolution of 15 km. For all systems, the ensemble spreads grew as the forecast time increased, and the ensemble mean improved the forecast errors compared with individual control forecasts in the verification against the analysis fields. However, each system exhibited individual characteristics according to the MEP method. Some participants used physical perturbation methods. The significance of these methods was confirmed by the verification. However, the mean error (ME) of the ensemble forecast in some systems was worse than that of the individual control forecast. This result suggests that it is necessary to pay careful attention to physical perturbations.

An Overview of the National Weather Service National Water Model

NASA Astrophysics Data System (ADS)

Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Feng, X.; Karsten, L. R.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.

2016-12-01

The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research (NCAR) and the NWS National Centers for Environmental Prediction (NCEP) recently implemented version 1.0 of the National Water Model (NWM) into operations. This model is an hourly cycling uncoupled analysis and forecast system that provides streamflow for 2.7 million river reaches and other hydrologic information on 1km and 250m grids. It will provide complementary hydrologic guidance at current NWS river forecast locations and significantly expand guidance coverage and type in underserved locations. The core of this system is the NCAR-supported community Weather Research and Forecasting (WRF)-Hydro hydrologic model. It ingests forcing from a variety of sources including Multi-Sensor Multi-Radar (MRMS) radar-gauge observed precipitation data and High Resolution Rapid Refresh (HRRR), Rapid Refresh (RAP), Global Forecast System (GFS) and Climate Forecast System (CFS) forecast data. WRF-Hydro is configured to use the Noah-Multi Parameterization (Noah-MP) Land Surface Model (LSM) to simulate land surface processes. Separate water routing modules perform diffusive wave surface routing and saturated subsurface flow routing on a 250m grid, and Muskingum-Cunge channel routing down National Hydrogaphy Dataset Plus V2 (NHDPlusV2) stream reaches. River analyses and forecasts are provided across a domain encompassing the Continental United States (CONUS) and hydrologically contributing areas, while land surface output is available on a larger domain that extends beyond the CONUS into Canada and Mexico (roughly from latitude 19N to 58N). The system includes an analysis and assimilation configuration along with three forecast configurations. These include a short-range 15 hour deterministic forecast, a medium-Range 10 day deterministic forecast and a long-range 30 day 16-member ensemble forecast. United Sates Geologic Survey (USGS) streamflow observations are assimilated into the analysis and assimilation configuration, and all four configurations benefit from the inclusion of 1,260 reservoirs. An overview of the National Water Model will be given, along with information on ongoing evaluation activities and plans for future NWM enhancements.

Calibration and combination of monthly near-surface temperature and precipitation predictions over Europe

NASA Astrophysics Data System (ADS)

Rodrigues, Luis R. L.; Doblas-Reyes, Francisco J.; Coelho, Caio A. S.

2018-02-01

A Bayesian method known as the Forecast Assimilation (FA) was used to calibrate and combine monthly near-surface temperature and precipitation outputs from seasonal dynamical forecast systems. The simple multimodel (SMM), a method that combines predictions with equal weights, was used as a benchmark. This research focuses on Europe and adjacent regions for predictions initialized in May and November, covering the boreal summer and winter months. The forecast quality of the FA and SMM as well as the single seasonal dynamical forecast systems was assessed using deterministic and probabilistic measures. A non-parametric bootstrap method was used to account for the sampling uncertainty of the forecast quality measures. We show that the FA performs as well as or better than the SMM in regions where the dynamical forecast systems were able to represent the main modes of climate covariability. An illustration with the near-surface temperature over North Atlantic, the Mediterranean Sea and Middle-East in summer months associated with the well predicted first mode of climate covariability is offered. However, the main modes of climate covariability are not well represented in most situations discussed in this study as the seasonal dynamical forecast systems have limited skill when predicting the European climate. In these situations, the SMM performs better more often.

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

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

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-10-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

Economic Value of Weather and Climate Forecasts

NASA Astrophysics Data System (ADS)

Katz, Richard W.; Murphy, Allan H.

1997-06-01

Weather and climate extremes can significantly impact the economics of a region. This book examines how weather and climate forecasts can be used to mitigate the impact of the weather on the economy. Interdisciplinary in scope, it explores the meteorological, economic, psychological, and statistical aspects of weather prediction. Chapters by area specialists provide a comprehensive view of this timely topic. They encompass forecasts over a wide range of temporal scales, from weather over the next few hours to the climate months or seasons ahead, and address the impact of these forecasts on human behavior. Economic Value of Weather and Climate Forecasts seeks to determine the economic benefits of existing weather forecasting systems and the incremental benefits of improving these systems, and will be an interesting and essential text for economists, statisticians, and meteorologists.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Shukla, Shraddhanand; Arsenault, Kristi R.; Getirana, Augusto; Kumar, Sujay V.; Roningen, Jeanne; Zaitchik, Ben; McNally, Amy; Koster, Randal D.; Peters-Lidard, Christa

2017-04-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. A seamless and effective monitoring and early warning system is needed by regional/national stakeholders. Such system should support a proactive drought management approach and mitigate the socio-economic losses up to the extent possible. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of the LIS models used for drought and water availability monitoring in the region. The second part will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the monitoring and forecasting products through NASA's web-services. The water deficit forecasting system thus far incorporates NOAA's Noah land surface model (LSM), version 3.3, the Variable Infiltration Capacity (VIC) model, version 4.12, NASA GMAO's Catchment LSM, and the Noah Multi-Physics (MP) LSM (the latter two incorporate prognostic water table schemes). In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. The LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. The LIS software framework integrates these forcing datasets and drives the four LSMs and HyMAP. The Land Verification Toolkit (LVT) is used for the evaluation of the LSMs, as it provides model ensemble metrics and the ability to compare against a variety of remotely sensed measurements, like different evapotranspiration (ET) and soil moisture products, and other reanalysis datasets that are available for this region. Comparison of the models' energy and hydrological budgets will be shown for this region (and sub-basin level, e.g., Blue Nile River) and time period (1981-2015), along with evaluating ET, streamflow, groundwater storage and soil moisture, using evaluation metrics (e.g., anomaly correlation, RMSE, etc.). The system uses seasonal climate forecasts from NASA's GMAO (the Goddard Earth Observing System Model, version 5) and NCEP's Climate Forecast System, version 2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region.

Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

2010-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy

NASA Astrophysics Data System (ADS)

Danhelka, Jan; Vlasak, Tomas

2010-05-01

Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive model operation, experience and forecasting strategy differs between responsible forecasting offices. Warning is based on model outputs interpretation by hydrologists-forecaster. Warning hit rate reached 0.60 for threshold set to lowest flood stage of which 0.11 was underestimation of flood degree (miss 0.22, false alarm 0.28). Critical success index of model forecast was 0.34, while the same criteria for warning reached 0.55. We assume that the increase accounts not only to change of scale from single forecasting point to region for warning, but partly also to forecaster's added value. There is no official warning strategy preferred in the Czech Republic (f.e. tolerance towards higher false alarm rate). Therefore forecaster decision and personal strategy is of great importance. Results show quite successful warning for 1st flood level exceedance, over-warning for 2nd flood level, but under-warning for 3rd (highest) flood level. That suggests general forecaster's preference of medium level warning (2nd flood level is legally determined to be the start of the flood and flood protection activities). In conclusion human forecaster's experience and analysis skill increases flood warning performance notably. However society preference should be specifically addressed in the warning strategy definition to support forecaster's decision making.

Precipitation forecasts for rainfall runoff predictions. A case study in poorly gauged Ribb and Gumara catchments, upper Blue Nile, Ethiopia

NASA Astrophysics Data System (ADS)

Seyoum, Mesgana; van Andel, Schalk Jan; Xuan, Yunqing; Amare, Kibreab

Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center’s-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.

An operational ensemble prediction system for catchment rainfall over eastern Africa spanning multiple temporal and spatial scales

NASA Astrophysics Data System (ADS)

Riddle, E. E.; Hopson, T. M.; Gebremichael, M.; Boehnert, J.; Broman, D.; Sampson, K. M.; Rostkier-Edelstein, D.; Collins, D. C.; Harshadeep, N. R.; Burke, E.; Havens, K.

2017-12-01

While it is not yet certain how precipitation patterns will change over Africa in the future, it is clear that effectively managing the available water resources is going to be crucial in order to mitigate the effects of water shortages and floods that are likely to occur in a changing climate. One component of effective water management is the availability of state-of-the-art and easy to use rainfall forecasts across multiple spatial and temporal scales. We present a web-based system for displaying and disseminating ensemble forecast and observed precipitation data over central and eastern Africa. The system provides multi-model rainfall forecasts integrated to relevant hydrological catchments for timescales ranging from one day to three months. A zoom-in features is available to access high resolution forecasts for small-scale catchments. Time series plots and data downloads with forecasts, recent rainfall observations and climatological data are available by clicking on individual catchments. The forecasts are calibrated using a quantile regression technique and an optimal multi-model forecast is provided at each timescale. The forecast skill at the various spatial and temporal scales will discussed, as will current applications of this tool for managing water resources in Sudan and optimizing hydropower operations in Ethiopia and Tanzania.

A Wind Forecasting System for Energy Application

NASA Astrophysics Data System (ADS)

Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

2010-05-01

Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

THE NEW ENGLAND AIR QUALITY FORECASTING PILOT PROGRAM: DEVELOPMENT OF AN EVALUATION PROTOCOL AND PERFORMANCE BENCHMARK

EPA Science Inventory

The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a "test bed" for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implemen...

Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

NASA Astrophysics Data System (ADS)

Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

2016-12-01

Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

Development of a flood early warning system and communication with end-users: the Vipava/Vipacco case study in the KULTURisk FP7 project

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Caronna, Paolo; Ranzi, Roberto

2014-05-01

Within the framework of risk communication, the goal of an early warning system is to support the interaction between technicians and authorities (and subsequently population) as a prevention measure. The methodology proposed in the KULTURisk FP7 project aimed to build a closer collaboration between these actors, in the perspective of promoting pro-active actions to mitigate the effects of flood hazards. The transnational (Slovenia/ Italy) Soča/Isonzo case study focused on this concept of cooperation between stakeholders and hydrological forecasters. The DIMOSHONG_VIP hydrological model was calibrated for the Vipava/Vipacco River (650 km2), a tributary of the Soča/Isonzo River, on the basis of flood events occurred between 1998 and 2012. The European Centre for Medium-Range Weather Forecasts (ECMWF) provided the past meteorological forecasts, both deterministic (1 forecast) and probabilistic (51 ensemble members). The resolution of the ECMWF grid is currently about 15 km (Deterministic-DET) and 30 km (Ensemble Prediction System-EPS). A verification was conducted to validate the flood-forecast outputs of the DIMOSHONG_VIP+ECMWF early warning system. Basic descriptive statistics, like event probability, probability of a forecast occurrence and frequency bias were determined. Some performance measures were calculated, such as hit rate (probability of detection) and false alarm rate (probability of false detection). Relative Opening Characteristic (ROC) curves were generated both for deterministic and probabilistic forecasts. These analysis showed a good performance of the early warning system, in respect of the small size of the sample. A particular attention was spent to the design of flood-forecasting output charts, involving and inquiring stakeholders (Alto Adriatico River Basin Authority), hydrology specialists in the field, and common people. Graph types for both forecasted precipitation and discharge were set. Three different risk thresholds were identified ("attention", "pre-alarm" or "alert", "alarm"), with an "icon-style" representation, suitable for communication to civil protection stakeholders or the public. Aiming at showing probabilistic representations in a "user-friendly" way, we opted for the visualization of the single deterministic forecasted hydrograph together with the 5%, 25%, 50%, 75% and 95% percentiles bands of the Hydrological Ensemble Prediction System (HEPS). HEPS is generally used for 3-5 days hydrological forecasts, while the error due to incorrect initial data is comparable to the error due to the lower resolution with respect to the deterministic forecast. In the short term forecasting (12-48 hours) the HEPS-members show obviously a similar tendency; in this case, considering its higher resolution, the deterministic forecast is expected to be more effective. The plot of different forecasts in the same chart allows the use of model outputs from 4/5 days to few hours before a potential flood event. This framework was built to help a stakeholder, like a mayor, a civil protection authority, etc, in the flood control and management operations, and was designed to be included in a wider decision support system.

A system for forecasting and monitoring cash flow : phase II, forecasting federal and state revenues, maintenance contracts, other expenditures, and cash balances.

DOT National Transportation Integrated Search

1985-01-01

The research on which this report is based was performed as part of a study to develop an improved system for generating a two-year forecast of monthly cash flows for the Virginia Department of Highways and Transportation. It revealed that current te...

Use of EOS Data in AWIPS for Weather Forecasting

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Haines, Stephanie L.; Suggs, Ron J.; Bradshaw, Tom; Darden, Chris; Burks, Jason

2003-01-01

Operational weather forecasting relies heavily on real time data and modeling products for forecast preparation and dissemination of significant weather information to the public. The synthesis of this information (observations and model products) by the meteorologist is facilitated by a decision support system to display and integrate the information in a useful fashion. For the NWS this system is called Advanced Weather Interactive Processing System (AWIPS). Over the last few years NASA has launched a series of new Earth Observation Satellites (EOS) for climate monitoring that include several instruments that provide high-resolution measurements of atmospheric and surface features important for weather forecasting and analysis. The key to the utilization of these unique new measurements by the NWS is the real time integration of the EOS data into the AWIPS system. This is currently being done in the Huntsville and Birmingham NWS Forecast Offices under the NASA Short-term Prediction Research and Transition (SPORT) Program. This paper describes the use of near real time MODIS and AIRS data in AWIPS to improve the detection of clouds, moisture variations, atmospheric stability, and thermal signatures that can lead to significant weather development. The paper and the conference presentation will focus on several examples where MODIS and AIRS data have made a positive impact on forecast accuracy. The results of an assessment of the utility of these products for weather forecast improvement made at the Huntsville NWS Forecast Office will be presented.

Multi-platform operational validation of the Western Mediterranean SOCIB forecasting system

NASA Astrophysics Data System (ADS)

Juza, Mélanie; Mourre, Baptiste; Renault, Lionel; Tintoré, Joaquin

2014-05-01

The development of science-based ocean forecasting systems at global, regional, and local scales can support a better management of the marine environment (maritime security, environmental and resources protection, maritime and commercial operations, tourism, ...). In this context, SOCIB (the Balearic Islands Coastal Observing and Forecasting System, www.socib.es) has developed an operational ocean forecasting system in the Western Mediterranean Sea (WMOP). WMOP uses a regional configuration of the Regional Ocean Modelling System (ROMS, Shchepetkin and McWilliams, 2005) nested in the larger scale Mediterranean Forecasting System (MFS) with a spatial resolution of 1.5-2km. WMOP aims at reproducing both the basin-scale ocean circulation and the mesoscale variability which is known to play a crucial role due to its strong interaction with the large scale circulation in this region. An operational validation system has been developed to systematically assess the model outputs at daily, monthly and seasonal time scales. Multi-platform observations are used for this validation, including satellite products (Sea Surface Temperature, Sea Level Anomaly), in situ measurements (from gliders, Argo floats, drifters and fixed moorings) and High-Frequency radar data. The validation procedures allow to monitor and certify the general realism of the daily production of the ocean forecasting system before its distribution to users. Additionally, different indicators (Sea Surface Temperature and Salinity, Eddy Kinetic Energy, Mixed Layer Depth, Heat Content, transports in key sections) are computed every day both at the basin-scale and in several sub-regions (Alboran Sea, Balearic Sea, Gulf of Lion). The daily forecasts, validation diagnostics and indicators from the operational model over the last months are available at www.socib.es.

Automated system for smoke dispersion prediction due to wild fires in Alaska

NASA Astrophysics Data System (ADS)

Kulchitsky, A.; Stuefer, M.; Higbie, L.; Newby, G.

2007-12-01

Community climate models have enabled development of specific environmental forecast systems. The University of Alaska (UAF) smoke group was created to adapt a smoke forecast system to the Alaska region. The US Forest Service (USFS) Missoula Fire Science Lab had developed a smoke forecast system based on the Weather Research and Forecasting (WRF) Model including chemistry (WRF/Chem). Following the successful experience of USFS, which runs their model operationally for the contiguous U.S., we develop a similar system for Alaska in collaboration with scientists from the USFS Missoula Fire Science Lab. Wildfires are a significant source of air pollution in Alaska because the climate and vegetation favor annual summer fires that burn huge areas. Extreme cases occurred in 2004, when an area larger than Maryland (more than 25000~km2) burned. Small smoke particles with a diameter less than 10~μm can penetrate deep into lungs causing health problems. Smoke also creates a severe restriction to air transport and has tremendous economical effect. The smoke dispersion and forecast system for Alaska was developed at the Geophysical Institute (GI) and the Arctic Region Supercomputing Center (ARSC), both at University of Alaska Fairbanks (UAF). They will help the public and plan activities a few days in advance to avoid dangerous smoke exposure. The availability of modern high performance supercomputers at ARSC allows us to create and run high-resolution, WRF-based smoke dispersion forecast for the entire State of Alaska. The core of the system is a Python program that manages the independent pieces. Our adapted Alaska system performs the following steps \\begin{itemize} Calculate the medium-resolution weather forecast using WRF/Met. Adapt the near real-time satellite-derived wildfire location and extent data that are received via direct broadcast from UAF's "Geographic Information Network of Alaska" (GINA) Calculate fuel moisture using WRF forecasts and National Fire Danger Rating System (NFDRS) fuel maps Calculate smoke emission components using a first order fire emission model Model the smoke plume rise yielding a vertically distribution that accounts for one-dimensional (vertical) concentrations of smoke constituents in the atmosphere above the fire Run WRF/Chem at high resolution for the forecast Use standard graphical tools to provide accessible smoke dispersion The system run twice each day at ARSC. The results will be freely available from a dedicated wildfire smoke web portal at ARSC.

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada's Regional Air Quality Deterministic Prediction System.

PubMed

So, Rita; Teakles, Andrew; Baik, Jonathan; Vingarzan, Roxanne; Jones, Keith

2018-05-01

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr. This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.

Road weather forecast quality analysis : project summary

DOT National Transportation Integrated Search

2006-03-01

The purpose of this research is to enhance the use of KDOTs Roadway Weather : Information System by improving the weather forecasts themselves and raising the level of : confidence in these forecasts.

A Unified Data Assimilation Strategy for Regional Coupled Atmosphere-Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xie, Lian; Liu, Bin; Zhang, Fuqing; Weng, Yonghui

2014-05-01

Improving tropical cyclone (TC) forecasts is a top priority in weather forecasting. Assimilating various observational data to produce better initial conditions for numerical models using advanced data assimilation techniques has been shown to benefit TC intensity forecasts, whereas assimilating large-scale environmental circulation into regional models by spectral nudging or Scale-Selective Data Assimilation (SSDA) has been demonstrated to improve TC track forecasts. Meanwhile, taking into account various air-sea interaction processes by high-resolution coupled air-sea modelling systems has also been shown to improve TC intensity forecasts. Despite the advances in data assimilation and air-sea coupled models, large errors in TC intensity and track forecasting remain. For example, Hurricane Nate (2011) has brought considerable challenge for the TC operational forecasting community, with very large intensity forecast errors (27, 25, and 40 kts for 48, 72, and 96 h, respectively) for the official forecasts. Considering the slow-moving nature of Hurricane Nate, it is reasonable to hypothesize that air-sea interaction processes played a critical role in the intensity change of the storm, and accurate representation of the upper ocean dynamics and thermodynamics is necessary to quantitatively describe the air-sea interaction processes. Currently, data assimilation techniques are generally only applied to hurricane forecasting in stand-alone atmospheric or oceanic model. In fact, most of the regional hurricane forecasting models only included data assimilation techniques for improving the initial condition of the atmospheric model. In such a situation, the benefit of adjustments in one model (atmospheric or oceanic) by assimilating observational data can be compromised by errors from the other model. Thus, unified data assimilation techniques for coupled air-sea modelling systems, which not only simultaneously assimilate atmospheric and oceanic observations into the coupled air-sea modelling system, but also nudging the large-scale environmental flow in the regional model towards global model forecasts are of increasing necessity. In this presentation, we will outline a strategy for an integrated approach in air-sea coupled data assimilation and discuss its benefits and feasibility from incremental results for select historical hurricane cases.

Extended Range Prediction of Indian Summer Monsoon: Current status

NASA Astrophysics Data System (ADS)

Sahai, A. K.; Abhilash, S.; Borah, N.; Joseph, S.; Chattopadhyay, R.; S, S.; Rajeevan, M.; Mandal, R.; Dey, A.

2014-12-01

The main focus of this study is to develop forecast consensus in the extended range prediction (ERP) of monsoon Intraseasonal oscillations using a suit of different variants of Climate Forecast system (CFS) model. In this CFS based Grand MME prediction system (CGMME), the ensemble members are generated by perturbing the initial condition and using different configurations of CFSv2. This is to address the role of different physical mechanisms known to have control on the error growth in the ERP in the 15-20 day time scale. The final formulation of CGMME is based on 21 ensembles of the standalone Global Forecast System (GFS) forced with bias corrected forecasted SST from CFS, 11 low resolution CFST126 and 11 high resolution CFST382. Thus, we develop the multi-model consensus forecast for the ERP of Indian summer monsoon (ISM) using a suite of different variants of CFS model. This coordinated international effort lead towards the development of specific tailor made regional forecast products over Indian region. Skill of deterministic and probabilistic categorical rainfall forecast as well the verification of large-scale low frequency monsoon intraseasonal oscillations has been carried out using hindcast from 2001-2012 during the monsoon season in which all models are initialized at every five days starting from 16May to 28 September. The skill of deterministic forecast from CGMME is better than the best participating single model ensemble configuration (SME). The CGMME approach is believed to quantify the uncertainty in both initial conditions and model formulation. Main improvement is attained in probabilistic forecast which is because of an increase in the ensemble spread, thereby reducing the error due to over-confident ensembles in a single model configuration. For probabilistic forecast, three tercile ranges are determined by ranking method based on the percentage of ensemble members from all the participating models falls in those three categories. CGMME further added value to both deterministic and probability forecast compared to raw SME's and this better skill is probably flows from large spread and improved spread-error relationship. CGMME system is currently capable of generating ER prediction in real time and successfully delivering its experimental operational ER forecast of ISM for the last few years.

An Assessment of the Subseasonal Forecast Performance in the Extended Global Ensemble Forecast System (GEFS)

NASA Astrophysics Data System (ADS)

Sinsky, E.; Zhu, Y.; Li, W.; Guan, H.; Melhauser, C.

2017-12-01

Optimal forecast quality is crucial for the preservation of life and property. Improving monthly forecast performance over both the tropics and extra-tropics requires attention to various physical aspects such as the representation of the underlying SST, model physics and the representation of the model physics uncertainty for an ensemble forecast system. This work focuses on the impact of stochastic physics, SST and the convection scheme on forecast performance for the sub-seasonal scale over the tropics and extra-tropics with emphasis on the Madden-Julian Oscillation (MJO). A 2-year period is evaluated using the National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS). Three experiments with different configurations than the operational GEFS were performed to illustrate the impact of the stochastic physics, SST and convection scheme. These experiments are compared against a control experiment (CTL) which consists of the operational GEFS but its integration is extended from 16 to 35 days. The three configurations are: 1) SPs, which uses a Stochastically Perturbed Physics Tendencies (SPPT), Stochastic Perturbed Humidity (SHUM) and Stochastic Kinetic Energy Backscatter (SKEB); 2) SPs+SST_bc, which uses a combination of SPs and a bias-corrected forecast SST from the NCEP Climate Forecast System Version 2 (CFSv2); and 3) SPs+SST_bc+SA_CV, which combines SPs, a bias-corrected forecast SST and a scale aware convection scheme. When comparing to the CTL experiment, SPs shows substantial improvement. The MJO skill has improved by about 4 lead days during the 2-year period. Improvement is also seen over the extra-tropics due to the updated stochastic physics, where there is a 3.1% and a 4.2% improvement during weeks 3 and 4 over the northern hemisphere and southern hemisphere, respectively. Improvement is also seen when the bias-corrected CFSv2 SST is combined with SPs. Additionally, forecast performance enhances when the scale aware convection scheme (SPs+SST_bc+SA_CV) is added, especially over the tropics. Among the three experiments, the SPs+SST_bc+SA_CV is the best configuration in MJO forecast skill.

Sensitivity of mesoscale-model forecast skill to some initial-data characteristics, data density, data position, analysis procedure and measurement error

NASA Technical Reports Server (NTRS)

Warner, Thomas T.; Key, Lawrence E.; Lario, Annette M.

1989-01-01

The effects of horizontal and vertical data resolution, data density, data location, different objective analysis algorithms, and measurement error on mesoscale-forecast accuracy are studied with observing-system simulation experiments. Domain-averaged errors are shown to generally decrease with time. It is found that the vertical distribution of error growth depends on the initial vertical distribution of the error itself. Larger gravity-inertia wave noise is produced in forecasts with coarser vertical data resolution. The use of a low vertical resolution observing system with three data levels leads to more forecast errors than moderate and high vertical resolution observing systems with 8 and 14 data levels. Also, with poor vertical resolution in soundings, the initial and forecast errors are not affected by the horizontal data resolution.

Countering Overseas Threats: DOD and State Need to Address Gaps in Monitoring of Security Equipment Transferred to Lebanon

DTIC Science & Technology

2014-02-01

the ISF—night vision devices and ceramic plates for bullet proof vests . With regard to these two articles, we found the following: • INL consulted...However, INL did not consult the directorate about ceramic plates , which INL provided for bullet proof vests that it transferred to the ISF in...did not consult with the directorate about the ceramic plates , INL officials said that INL would contact the directorate in the future about any

Selection of Dimensions for an Anthropometric Data Base. Volume 2. Dimension Evaluation Sheets

DTIC Science & Technology

1986-05-30

RATING IN D IS: This dimension has not been identified as being useful for engineering anthropometry . F. RACE SENSITIVE? YES F-i NO Ffl GENDER SENSITIVE...SENSITIVE? YES NO[ Xl IN WHAT WAY? G. REPRODUCIBILITY: A f-W B [] C E-1 IF B OR C, THE PROBLEM IS: H. PARTICULARLY SENSITIVE FO: identification of...Marginal VALUE FOR A U.S. ARMY ANTHROPOMETRIC DATA BASE. D. REASON FOR RATING IN C ISf there is no engineering anthropometry application for this

Security in Iraq: A Framework for Analyzing Emerging Threats as U.S. Forces Leave

DTIC Science & Technology

2010-01-01

5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES...including enhance - ment of the ISF. Economic hardship in Iraq could increase the propen- sity for violence, especially if inequities are severe and...withdrawal of U.S. forces, if mutually agreed, should have three missions: xviii Security in Iraq • capability-building: aiding in the training

Visualizing One-Dimensional Electronic States and their Scattering in Semi-conducting Nanowires

NASA Astrophysics Data System (ADS)

Beidenkopf, Haim; Reiner, Jonathan; Norris, Andrew; Nayak, Abhay Kumar; Avraham, Nurit; Shtrikman, Hadas

One-dimensional electronic systems constitute a fascinating playground for the emergence of exotic electronic effects and phases, within and beyond the Tomonaga-Luttinger liquid paradigm. More recently topological superconductivity and Majorana modes were added to that long list of phenomena. We report scanning tunneling microscopy and spectroscopy measurements conducted on pristine, epitaxialy grown InAs nanowires. We resolve the 1D electronic band structure manifested both via Van-Hove singularities in the local density-of-states, as well as by the quasi-particle interference patterns, induced by scattering from surface impurities. By studying the scattering of the one-dimensional electronic states off various scatterers, including crystallographic defects and the nanowire end, we identify new one-dimensional relaxation regimes and yet unexplored effects of interactions. Some of these may bear implications on the topological superconducting state and Majorana modes therein. The authors acknowledge support from the Israeli Science Foundation (ISF).

Evaluation of Air Force and Navy Demand Forecasting Systems

DTIC Science & Technology

1994-01-01

forecasting approach, the Air Force Material Command is questioning the adoption of the Navy’s Statistical Demand Forecasting System ( Gitman , 1994). The...Recoverable Item Process in the Requirements Data Bank System is to manage reparable spare parts ( Gitman , 1994). Although RDB will have the capability of...D062) ( Gitman , 1994). Since a comparison is made to address Air Force concerns, this research only limits its analysis to the range of Air Force

Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

DTIC Science & Technology

2015-02-01

WRF ) Model using a Geographic Information System (GIS) by Jeffrey A Smith, Theresa A Foley, John W Raby, and Brian Reen...ARL-TR-7212 ● FEB 2015 US Army Research Laboratory Investigating Surface Bias Errors in the Weather Research and Forecasting ( WRF ) Model...SUBTITLE Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) Model using a Geographic Information System (GIS) 5a

Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts

NASA Astrophysics Data System (ADS)

Shastri, Hiteshri; Ghosh, Subimal; Karmakar, Subhankar

2017-02-01

Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e.g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning.

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

How much are you prepared to PAY for a forecast?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

2015-04-01

Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

Seasonal Forecast Skill And Teleconnections Over East Africa

NASA Astrophysics Data System (ADS)

MacLeod, D.; Palmer, T.

2017-12-01

Many people living in East Africa are significantly exposed to risks arising from climate variability. The region experiences two rainy seasons and poor performance of either or both of these (such as seen recently in 2016/17) reduces agricultural productivity and threatens food security. In combination with other factors this can lead to famine. By utilizing seasonal climate forecasts, preparatory actions can be taken in order to mitigate the risks arising from such climate variability. As part of the project ForPAc: "Towards forecast-based preparedness action", we are working with humanitarian agencies in Kenya to build such early warning systems on subseasonal-to-seasonal timescales. Here, the seasonal predictability and forecast skill of the two East African rainy seasons will be presented. Results from the new ECMWF operational forecasting system SEAS5 will be shown and compared to the previous System 4. Analysis of a new 110 year long atmosphere-only simulation will also be discussed, demonstrating impacts of atmosphere-ocean coupling as well as putting operational forecast skill in a long-term context. Particular focus will be given to the model representation of teleconnections of seasonal climate with global sea surface temperatures; highlighting sources of forecast error and informing future model development.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

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

Jiang, Huaiguang; Ding, Fei; Zhang, Yingchen

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution systemmore » operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.« less

Ocean state and uncertainty forecasts using HYCOM with Local Ensemble Transfer Kalman Filter (LETKF)

NASA Astrophysics Data System (ADS)

Wei, Mozheng; Hogan, Pat; Rowley, Clark; Smedstad, Ole-Martin; Wallcraft, Alan; Penny, Steve

2017-04-01

An ensemble forecast system based on the US Navy's operational HYCOM using Local Ensemble Transfer Kalman Filter (LETKF) technology has been developed for ocean state and uncertainty forecasts. One of the advantages is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates the operational observations using ensemble method. The background covariance during this assimilation process is supplied with the ensemble, thus it avoids the difficulty of developing tangent linear and adjoint models for 4D-VAR from the complicated hybrid isopycnal vertical coordinate in HYCOM. Another advantage is that the ensemble system provides the valuable uncertainty estimate corresponding to every state forecast from HYCOM. Uncertainty forecasts have been proven to be critical for the downstream users and managers to make more scientifically sound decisions in numerical prediction community. In addition, ensemble mean is generally more accurate and skilful than the single traditional deterministic forecast with the same resolution. We will introduce the ensemble system design and setup, present some results from 30-member ensemble experiment, and discuss scientific, technical and computational issues and challenges, such as covariance localization, inflation, model related uncertainties and sensitivity to the ensemble size.

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

NASA Astrophysics Data System (ADS)

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. Later on, post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS) were implemented into OST. These forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. This presentation will highlight the benefits of the improved forecasts using examples from actual system operations.

OAST system technology planning

NASA Technical Reports Server (NTRS)

Sadin, S. R.

1978-01-01

The NASA Office of Aeronautics and Space Technology developed a planning model for space technology consisting of a space systems technology model, technology forecasts and technology surveys. The technology model describes candidate space missions through the year 2000 and identifies their technology requirements. The technology surveys and technology forecasts provide, respectively, data on the current status and estimates of the projected status of relevant technologies. These tools are used to further the understanding of the activities and resources required to ensure the timely development of technological capabilities. Technology forecasting in the areas of information systems, spacecraft systems, transportation systems, and power systems are discussed.

A Comparison Study of Two Numerical Tsunami Forecasting Systems

NASA Astrophysics Data System (ADS)

Greenslade, Diana J. M.; Titov, Vasily V.

2008-12-01

This paper presents a comparison of two tsunami forecasting systems: the NOAA/PMEL system (SIFT) and the Australian Bureau of Meteorology system (T1). Both of these systems are based on a tsunami scenario database and both use the same numerical model. However, there are some major differences in the way in which the scenarios are constructed and in the implementation of the systems. Two tsunami events are considered here: Tonga 2006 and Sumatra 2007. The results show that there are some differences in the distribution of maximum wave amplitude, particularly for the Tonga event, however both systems compare well to the available tsunameter observations. To assess differences in the forecasts for coastal amplitude predictions, the offshore forecast results from both systems were used as boundary conditions for a high-resolution model for Hilo, Hawaii. The minor differences seen between the two systems in deep water become considerably smaller at the tide gauge and both systems compare very well with the observations.

Calibration and combination of dynamical seasonal forecasts to enhance the value of predicted probabilities for managing risk

NASA Astrophysics Data System (ADS)

Dutton, John A.; James, Richard P.; Ross, Jeremy D.

2013-06-01

Seasonal probability forecasts produced with numerical dynamics on supercomputers offer great potential value in managing risk and opportunity created by seasonal variability. The skill and reliability of contemporary forecast systems can be increased by calibration methods that use the historical performance of the forecast system to improve the ongoing real-time forecasts. Two calibration methods are applied to seasonal surface temperature forecasts of the US National Weather Service, the European Centre for Medium Range Weather Forecasts, and to a World Climate Service multi-model ensemble created by combining those two forecasts with Bayesian methods. As expected, the multi-model is somewhat more skillful and more reliable than the original models taken alone. The potential value of the multimodel in decision making is illustrated with the profits achieved in simulated trading of a weather derivative. In addition to examining the seasonal models, the article demonstrates that calibrated probability forecasts of weekly average temperatures for leads of 2-4 weeks are also skillful and reliable. The conversion of ensemble forecasts into probability distributions of impact variables is illustrated with degree days derived from the temperature forecasts. Some issues related to loss of stationarity owing to long-term warming are considered. The main conclusion of the article is that properly calibrated probabilistic forecasts possess sufficient skill and reliability to contribute to effective decisions in government and business activities that are sensitive to intraseasonal and seasonal climate variability.

A quality assessment of the MARS crop yield forecasting system for the European Union

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Bareuth, Bettina

2015-04-01

Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt events. We describe the methodology and present seasonal and inter-basin variations in DA-enhanced forecast skill.

Better Forecasting for Better Planning: A Systems Approach.

ERIC Educational Resources Information Center

Austin, W. Burnet

Predictions and forecasts are the most critical features of rational planning as well as the most vulnerable to inaccuracy. Because plans are only as good as their forecasts, current planning procedures could be improved by greater forecasting accuracy. Economic factors explain and predict more than any other set of factors, making economic…

Solar and Wind Forecasting | Grid Modernization | NREL

Science.gov Websites

and Wind Forecasting Solar and Wind Forecasting As solar and wind power become more common system operators. An aerial photo of the National Wind Technology Center's PV arrays. Capabilities value of accurate forecasting Wind power visualization to direct questions and feedback during industry

Research on light rail electric load forecasting based on ARMA model

NASA Astrophysics Data System (ADS)

Huang, Yifan

2018-04-01

The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

Evaluation of the Plant-Craig stochastic convection scheme in an ensemble forecasting system

NASA Astrophysics Data System (ADS)

Keane, R. J.; Plant, R. S.; Tennant, W. J.

2015-12-01

The Plant-Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic element only, from random parameter variation. A set of 34 ensemble forecasts, each with 24 members, is considered, over the month of July 2009. Deterministic and probabilistic measures of the precipitation forecasts are assessed. The Plant-Craig parameterization is found to improve probabilistic forecast measures, particularly the results for lower precipitation thresholds. The impact on deterministic forecasts at the grid scale is neutral, although the Plant-Craig scheme does deliver improvements when forecasts are made over larger areas. The improvements found are greater in conditions of relatively weak synoptic forcing, for which convective precipitation is likely to be less predictable.

Parametric analysis of parameters for electrical-load forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Gerber, William J.; Gonzalez, Avelino J.; Georgiopoulos, Michael

1997-04-01

Accurate total system electrical load forecasting is a necessary part of resource management for power generation companies. The better the hourly load forecast, the more closely the power generation assets of the company can be configured to minimize the cost. Automating this process is a profitable goal and neural networks should provide an excellent means of doing the automation. However, prior to developing such a system, the optimal set of input parameters must be determined. The approach of this research was to determine what those inputs should be through a parametric study of potentially good inputs. Input parameters tested were ambient temperature, total electrical load, the day of the week, humidity, dew point temperature, daylight savings time, length of daylight, season, forecast light index and forecast wind velocity. For testing, a limited number of temperatures and total electrical loads were used as a basic reference input parameter set. Most parameters showed some forecasting improvement when added individually to the basic parameter set. Significantly, major improvements were exhibited with the day of the week, dew point temperatures, additional temperatures and loads, forecast light index and forecast wind velocity.

Application of global weather and climate model output to the design and operation of wind-energy systems

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

Curry, Judith

This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatorymore » environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.« less

SONARC: A Sea Ice Monitoring and Forecasting System to Support Safe Operations and Navigation in Arctic Seas

NASA Astrophysics Data System (ADS)

Stephenson, S. R.; Babiker, M.; Sandven, S.; Muckenhuber, S.; Korosov, A.; Bobylev, L.; Vesman, A.; Mushta, A.; Demchev, D.; Volkov, V.; Smirnov, K.; Hamre, T.

2015-12-01

Sea ice monitoring and forecasting systems are important tools for minimizing accident risk and environmental impacts of Arctic maritime operations. Satellite data such as synthetic aperture radar (SAR), combined with atmosphere-ice-ocean forecasting models, navigation models and automatic identification system (AIS) transponder data from ships are essential components of such systems. Here we present first results from the SONARC project (project term: 2015-2017), an international multidisciplinary effort to develop novel and complementary ice monitoring and forecasting systems for vessels and offshore platforms in the Arctic. Automated classification methods (Zakhvatkina et al., 2012) are applied to Sentinel-1 dual-polarization SAR images from the Barents and Kara Sea region to identify ice types (e.g. multi-year ice, level first-year ice, deformed first-year ice, new/young ice, open water) and ridges. Short-term (1-3 days) ice drift forecasts are computed from SAR images using feature tracking and pattern tracking methods (Berg & Eriksson, 2014). Ice classification and drift forecast products are combined with ship positions based on AIS data from a selected period of 3-4 weeks to determine optimal vessel speed and routing in ice. Results illustrate the potential of high-resolution SAR data for near-real-time monitoring and forecasting of Arctic ice conditions. Over the next 3 years, SONARC findings will contribute new knowledge about sea ice in the Arctic while promoting safe and cost-effective shipping, domain awareness, resource management, and environmental protection.

Nowcasting of rainfall and of combined sewage flow in urban drainage systems.

PubMed

Achleitner, Stefan; Fach, Stefan; Einfalt, Thomas; Rauch, Wolfgang

2009-01-01

Nowcasting of rainfall may be used additionally to online rain measurements to optimize the operation of urban drainage systems. Uncertainties quoted for the rain volume are in the range of 5% to 10% mean square error (MSE), where for rain intensities 45% to 75% MSE are noted. For larger forecast periods up to 3 hours, the uncertainties will increase up to some hundred percents. Combined with the growing number of real time control concepts in sewer systems, rainfall forecast is used more and more in urban drainage systems. Therefore it is of interest how the uncertainties influence the final evaluation of a defined objective function. Uncertainty levels associated with the forecast itself are not necessarily transferable to resulting uncertainties in the catchment's flow dynamics. The aim of this paper is to analyse forecasts of rainfall and specific sewer output variables. For this study the combined sewer system of the city of Linz in the northern part of Austria located on the Danube has been selected. The city itself represents a total area of 96 km2 with 39 municipalities connected. It was found that the available weather radar data leads to large deviations in the forecast for precipitation at forecast horizons larger than 90 minutes. The same is true for sewer variables such a CSO overflow for small sub-catchments. Although the results improve for larger spatial scales, acceptable levels at forecast horizons larger than 90 minutes are not reached.

Operational coupled atmosphere - ocean - ice forecast system for the Gulf of St. Lawrence, Canada

NASA Astrophysics Data System (ADS)

Faucher, M.; Roy, F.; Desjardins, S.; Fogarty, C.; Pellerin, P.; Ritchie, H.; Denis, B.

2009-09-01

A fully interactive coupled atmosphere-ocean-ice forecasting system for the Gulf of St. Lawrence (GSL) has been running in experimental mode at the Canadian Meteorological Centre (CMC) for the last two winter seasons. The goal of this project is to provide more accurate weather and sea ice forecasts over the GSL and adjacent coastal areas by including atmosphere-oceanice interactions in the CMC operational forecast system using a formal coupling strategy between two independent modeling components. The atmospheric component is the Canadian operational GEM model (Côté et al. 1998) and the oceanic component is the ocean-ice model for the Gulf of St. Lawrence developed at the Maurice Lamontagne Institute (IML) (Saucier et al. 2003, 2004). The coupling between those two models is achieved by exchanging surface fluxes and variables through MPI communication. The re-gridding of the variables is done with a package developed at the Recherche en Prevision Numerique centre (RPN, Canada). Coupled atmosphere - ocean - ice forecasts are issued once a day based on 00GMT data. Results for the past two years have demonstrated that the coupled system produces improved forecasts in and around the GSL during all seasons, proving that atmosphere-ocean-ice interactions are indeed important even for short-term Canadian weather forecasts. This has important implications for other coupled modeling and data assimilation partnerships that are in progress involving EC, the Department of Fisheries and Oceans (DFO) and the National Defense (DND). Following this experimental phase, it is anticipated that this GSL system will be the first fully interactive coupled system to be implemented at CMC.

Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System

NASA Astrophysics Data System (ADS)

Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum

2017-04-01

ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i.e. convective precipitation ratio, speed of steering winds, CAPE - Convective Available Potential Energy - and solar radiation), alongside the rainfall forecasts themselves, to define the "weather types" that in turn define the expected sub-grid variability. The calibration and computational strategy intrinsic to the system will be illustrated. The quality of the global point rainfall forecasts is also illustrated by analysing recent case studies in which extreme totals and a greatly elevated flash flood risk could be foreseen some days in advance but especially by a longer-term verification that arises out of retrospective global point rainfall forecasting for 2016. The second phase, currently in development, is focussing on the relationships with other relevant geographical aspects, for instance, orography and coastlines. Preliminary results will be presented. These are promising but need further study to fully understand their impact on the spatial distribution of point rainfall totals.

Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

NASA Astrophysics Data System (ADS)

Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

2014-12-01

Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought, NMME SPI forecasts perform well in predicting drought severity and spatial patterns. For fast-developing drought events, such as the 2013 Upper Midwest flash drought, the system failed to capture the onset of the drought.

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

PubMed

Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

2016-01-01

Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

Flood Warning and Forecasting System in Slovakia

NASA Astrophysics Data System (ADS)

Leskova, Danica

2016-04-01

In 2015, it finished project Flood Warning and Forecasting System (POVAPSYS) as part of the flood protection in Slovakia till 2010. The aim was to build POVAPSYS integrated computerized flood forecasting and warning system. It took a qualitatively higher level of output meteorological and hydrological services in case of floods affecting large territorial units, as well as local flood events. It is further unfolding demands on performance and coordination of meteorological and hydrological services, troubleshooting observation, evaluation of data, fast communication, modeling and forecasting of meteorological and hydrological processes. Integration of all information entering and exiting to and from the project POVAPSYS provides Hydrological Flood Forecasting System (HYPOS). The system provides information on the current hydrometeorological situation and its evolution with the generation of alerts and notifications in case of exceeding predefined thresholds. HYPOS's functioning of the system requires flawless operability in critical situations while minimizing the loss of its key parts. HYPOS is a core part of the project POVAPSYS, it is a comprehensive software solutions based on a modular principle, providing data and processed information including alarms, in real time. In order to achieve full functionality of the system, in proposal, we have put emphasis on reliability, robustness, availability and security.

Post LANDSAT D Advanced Concept Evaluation (PLACE). [with emphasis on mission planning, technological forecasting, and user requirements

NASA Technical Reports Server (NTRS)

1977-01-01

An outline is given of the mission objectives and requirements, system elements, system concepts, technology requirements and forecasting, and priority analysis for LANDSAT D. User requirements and mission analysis and technological forecasting are emphasized. Mission areas considered include agriculture, range management, forestry, geology, land use, water resources, environmental quality, and disaster assessment.

Global scale predictability of floods

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek

2016-04-01

Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.

Demonstrating the Alaska Ocean Observing System in Prince William Sound

NASA Astrophysics Data System (ADS)

Schoch, G. Carl; McCammon, Molly

2013-07-01

The Alaska Ocean Observing System and the Oil Spill Recovery Institute developed a demonstration project over a 5 year period in Prince William Sound. The primary goal was to develop a quasi-operational system that delivers weather and ocean information in near real time to diverse user communities. This observing system now consists of atmospheric and oceanic sensors, and a new generation of computer models to numerically simulate and forecast weather, waves, and ocean circulation. A state of the art data management system provides access to these products from one internet portal at http://www.aoos.org. The project culminated in a 2009 field experiment that evaluated the observing system and performance of the model forecasts. Observations from terrestrial weather stations and weather buoys validated atmospheric circulation forecasts. Observations from wave gages on weather buoys validated forecasts of significant wave heights and periods. There was an emphasis on validation of surface currents forecasted by the ocean circulation model for oil spill response and search and rescue applications. During the 18 day field experiment a radar array mapped surface currents and drifting buoys were deployed. Hydrographic profiles at fixed stations, and by autonomous vehicles along transects, were made to acquire measurements through the water column. Terrestrial weather stations were the most reliable and least costly to operate, and in situ ocean sensors were more costly and considerably less reliable. The radar surface current mappers were the least reliable and most costly but provided the assimilation and validation data that most improved ocean circulation forecasts. We describe the setting of Prince William Sound and the various observational platforms and forecast models of the observing system, and discuss recommendations for future development.

AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, W.K.; Susskind, J.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Rosenburg, R.; Fuentes, M.

2009-01-01

Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

Study on Battery Capacity for Grid-connection Power Planning with Forecasts in Clustered Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Shimada, Takae; Kawasaki, Norihiro; Ueda, Yuzuru; Sugihara, Hiroyuki; Kurokawa, Kosuke

This paper aims to clarify the battery capacity required by a residential area with densely grid-connected photovoltaic (PV) systems. This paper proposes a planning method of tomorrow's grid-connection power from/to the external electric power system by using demand power forecasting and insolation forecasting for PV power predictions, and defines a operation method of the electricity storage device to control the grid-connection power as planned. A residential area consisting of 389 houses consuming 2390 MWh/year of electricity with 2390kW PV systems is simulated based on measured data and actual forecasts. The simulation results show that 8.3MWh of battery capacity is required in the conditions of half-hour planning and 1% or less of planning error ratio and PV output limiting loss ratio. The results also show that existing technologies of forecasting reduce required battery capacity to 49%, and increase the allowable installing PV amount to 210%.

Sub-seasonal predictability of water scarcity at global and local scale

NASA Astrophysics Data System (ADS)

Wanders, N.; Wada, Y.; Wood, E. F.

2016-12-01

Forecasting the water demand and availability for agriculture and energy production has been neglected in previous research, partly due to the fact that most large-scale hydrological models lack the skill to forecast human water demands at sub-seasonal time scale. We study the potential of a sub-seasonal water scarcity forecasting system for improved water management decision making and improved estimates of water demand and availability. We have generated 32 years of global sub-seasonal multi-model water availability, demand and scarcity forecasts. The quality of the forecasts is compared to a reference forecast derived from resampling historic weather observations. The newly developed system has been evaluated for both the global scale and in a real-time local application in the Sacramento valley for the Trinity, Shasta and Oroville reservoirs, where the water demand for agriculture and hydropower is high. On the global scale we find that the reference forecast shows high initial forecast skill (up to 8 months) for water scarcity in the eastern US, Central Asia and Sub-Saharan Africa. Adding dynamical sub-seasonal forecasts results in a clear improvement for most regions in the world, increasing the forecasts' lead time by 2 or more months on average. The strongest improvements are found in the US, Brazil, Central Asia and Australia. For the Sacramento valley we can accurately predict anomalies in the reservoir inflow, hydropower potential and the downstream irrigation water demand 6 months in advance. This allow us to forecast potential water scarcity in the Sacramento valley and adjust the reservoir management to prevent deficits in energy or irrigation water availability. The newly developed forecast system shows that it is possible to reduce the vulnerability to upcoming water scarcity events and allows optimization of the distribution of the available water between the agricultural and energy sector half a year in advance.

Pathways to designing and running an operational flood forecasting system: an adventure game!

NASA Astrophysics Data System (ADS)

Arnal, Louise; Pappenberger, Florian; Ramos, Maria-Helena; Cloke, Hannah; Crochemore, Louise; Giuliani, Matteo; Aalbers, Emma

2017-04-01

In the design and building of an operational flood forecasting system, a large number of decisions have to be taken. These include technical decisions related to the choice of the meteorological forecasts to be used as input to the hydrological model, the choice of the hydrological model itself (its structure and parameters), the selection of a data assimilation procedure to run in real-time, the use (or not) of a post-processor, and the computing environment to run the models and display the outputs. Additionally, a number of trans-disciplinary decisions are also involved in the process, such as the way the needs of the users will be considered in the modelling setup and how the forecasts (and their quality) will be efficiently communicated to ensure usefulness and build confidence in the forecasting system. We propose to reflect on the numerous, alternative pathways to designing and running an operational flood forecasting system through an adventure game. In this game, the player is the protagonist of an interactive story driven by challenges, exploration and problem-solving. For this presentation, you will have a chance to play this game, acting as the leader of a forecasting team at an operational centre. Your role is to manage the actions of your team and make sequential decisions that impact the design and running of the system in preparation to and during a flood event, and that deal with the consequences of the forecasts issued. Your actions are evaluated by how much they cost you in time, money and credibility. Your aim is to take decisions that will ultimately lead to a good balance between time and money spent, while keeping your credibility high over the whole process. This game was designed to highlight the complexities behind decision-making in an operational forecasting and emergency response context, in terms of the variety of pathways that can be selected as well as the timescale, cost and timing of effective actions.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, Elizabeth; Wood, Andy; Nijssen, Bart; Mendoza, Pablo; Newman, Andy; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

In an automated forecast system, hydrologic data assimilation (DA) performs the valuable function of correcting raw simulated watershed model states to better represent external observations, including measurements of streamflow, snow, soil moisture, and the like. Yet the incorporation of automated DA into operational forecasting systems has been a long-standing challenge due to the complexities of the hydrologic system, which include numerous lags between state and output variations. To help demonstrate that such methods can succeed in operational automated implementations, we present results from the real-time application of an ensemble particle filter (PF) for short-range (7 day lead) ensemble flow forecasts in western US river basins. We use the System for Hydromet Applications, Research and Prediction (SHARP), developed by the National Center for Atmospheric Research (NCAR) in collaboration with the University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. SHARP is a fully automated platform for short-term to seasonal hydrologic forecasting applications, incorporating uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions through ensemble methods. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 temperature and precipitation time series through conceptual and physically-oriented models. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. The PF selects and/or weights and resamples the IHCs that are most consistent with external streamflow observations, and uses the particles to initialize a streamflow forecast ensemble driven by ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS). We apply this method in real-time for several basins in the western US that are important for water resources management, and perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts skill. This presentation describes findings, including a comparison of sequential and non-sequential particle weighting methods.

The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

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

Wang, Qin; Wu, Hongyu; Florita, Anthony R.

The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was comparedmore » through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.« less

The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

DOE PAGES

Wang, Qin; Wu, Hongyu; Florita, Anthony R.; ...

2016-11-11

The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was comparedmore » through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.« less

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model.

PubMed

Wang, Jianzhou; Niu, Tong; Wang, Rui

2017-03-02

The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

Projecting technology change to improve space technology planning and systems management

NASA Astrophysics Data System (ADS)

Walk, Steven Robert

2011-04-01

Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

PubMed Central

Wang, Jianzhou; Niu, Tong; Wang, Rui

2017-01-01

The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable. PMID:28257122

AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, W. K.; Susskind, J.; Rosenberg, R.

2011-01-01

A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

NASA Technical Reports Server (NTRS)

Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

2016-01-01

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

Evaluation of a Wildfire Smoke Forecasting System as a Tool for Public Health Protection

PubMed Central

Brauer, Michael; Henderson, Sarah B.

2013-01-01

Background: Exposure to wildfire smoke has been associated with cardiopulmonary health impacts. Climate change will increase the severity and frequency of smoke events, suggesting a need for enhanced public health protection. Forecasts of smoke exposure can facilitate public health responses. Objectives: We evaluated the utility of a wildfire smoke forecasting system (BlueSky) for public health protection by comparing its forecasts with observations and assessing their associations with population-level indicators of respiratory health in British Columbia, Canada. Methods: We compared BlueSky PM2.5 forecasts with PM2.5 measurements from air quality monitors, and BlueSky smoke plume forecasts with plume tracings from National Oceanic and Atmospheric Administration Hazard Mapping System remote sensing data. Daily counts of the asthma drug salbutamol sulfate dispensations and asthma-related physician visits were aggregated for each geographic local health area (LHA). Daily continuous measures of PM2.5 and binary measures of smoke plume presence, either forecasted or observed, were assigned to each LHA. Poisson regression was used to estimate the association between exposure measures and health indicators. Results: We found modest agreement between forecasts and observations, which was improved during intense fire periods. A 30-μg/m3 increase in BlueSky PM2.5 was associated with an 8% increase in salbutamol dispensations and a 5% increase in asthma-related physician visits. BlueSky plume coverage was associated with 5% and 6% increases in the two health indicators, respectively. The effects were similar for observed smoke, and generally stronger in very smoky areas. Conclusions: BlueSky forecasts showed modest agreement with retrospective measures of smoke and were predictive of respiratory health indicators, suggesting they can provide useful information for public health protection. Citation: Yao J, Brauer M, Henderson SB. 2013. Evaluation of a wildfire smoke forecasting system as a tool for public health protection. Environ Health Perspect 121:1142–1147; http://dx.doi.org/10.1289/ehp.1306768 PMID:23906969

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

DTIC Science & Technology

2010-09-30

In part 2 (Bonazzi et al., 2010), the impact of the ensemble forecast methodology based on MFS-Wind-BHM perturbations is documented. Forecast...absence of dt data stage inputs, the forecast impact of MFS-Error-BHM is neutral. Experiments are underway now to introduce dt back into the MFS-Error...BHM and quantify forecast impacts at MFS. MFS-SuperEnsemble-BHM We have assembled all needed datasets and completed algorithmic development

A forecasting model for power consumption of high energy-consuming industries based on system dynamics

NASA Astrophysics Data System (ADS)

Zhou, Zongchuan; Dang, Dongsheng; Qi, Caijuan; Tian, Hongliang

2018-02-01

It is of great significance to make accurate forecasting for the power consumption of high energy-consuming industries. A forecasting model for power consumption of high energy-consuming industries based on system dynamics is proposed in this paper. First, several factors that have influence on the development of high energy-consuming industries in recent years are carefully dissected. Next, by analysing the relationship between each factor and power consumption, the system dynamics flow diagram and equations are set up to reflect the relevant relationships among variables. In the end, the validity of the model is verified by forecasting the power consumption of electrolytic aluminium industry in Ningxia according to the proposed model.

Forecasting sea fog on the coast of southern China

NASA Astrophysics Data System (ADS)

Huang, H.; Huang, B.; Liu, C.; Tu, J.; Wen, G.; Mao, W.

2016-12-01

Forecast sea fog is still full of challenges. We have performed the numerical forecasting of sea fog on the coast of southern China by using the operational meso-scale regional model GRAPES (Global/Regional assimilation and prediction system). The GRAPES model horizontal resolution was 3km and with 66 vertical levels. A total of 72 hours forecasting of sea fog was conducted with hourly outputs over the sea fog event. The results show that the model system can predict reasonable characteristics of typical sea fog events on the coast of southern China. The scope of sea fog coincides with the observations of meteorological stations, the observations of the Marine Meteorological Science Experiment Base (MMSEB) at Bohe, Maoming and satellite products of sea fog. The goal of this study is to establish an operational numerical forecasting model system of sea fog on the coast of southern China.

Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

NASA Astrophysics Data System (ADS)

Wu, Qi

2010-03-01

Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

Routine High-Resolution Forecasts/Analyses for the Pacific Disaster Center: User Manual

NASA Technical Reports Server (NTRS)

Roads, John; Han, J.; Chen, S.; Burgan, R.; Fujioka, F.; Stevens, D.; Funayama, D.; Chambers, C.; Bingaman, B.; McCord, C.;

Three-model ensemble wind prediction in southern Italy

NASA Astrophysics Data System (ADS)

Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo

2016-03-01

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

An Enhanced Convective Forecast (ECF) for the New York TRACON Area

NASA Technical Reports Server (NTRS)

Wheeler, Mark; Stobie, James; Gillen, Robert; Jedlovec, Gary; Sims, Danny

2008-01-01

In an effort to relieve summer-time congestion in the NY Terminal Radar Approach Control (TRACON) area, the FAA is testing an enhanced convective forecast (ECF) product. The test began in June 2008 and is scheduled to run through early September. The ECF is updated every two hours, right before the Air Traffic Control System Command Center (ATCSCC) national planning telcon. It is intended to be used by traffic managers throughout the National Airspace System (NAS) and airlines dispatchers to supplement information from the Collaborative Convective Forecast Product (CCFP) and the Corridor Integrated Weather System (CIWS). The ECF begins where the current CIWS forecast ends at 2 hours and extends out to 12 hours. Unlike the CCFP it is a detailed deterministic forecast with no aerial coverage limits. It is created by an ENSCO forecaster using a variety of guidance products including, the Weather Research and Forecast (WRF) model. This is the same version of the WRF that ENSCO runs over the Florida peninsula in support of launch operations at the Kennedy Space Center. For this project, the WRF model domain has been shifted to the Northeastern US. Several products from the NASA SPoRT group are also used by the ENSCO forecaster. In this paper we will provide examples of the ECF products and discuss individual cases of traffic management actions using ECF guidance.

Enhancing Community Based Early Warning Systems in Nepal with Flood Forecasting Using Local and Global Models

NASA Astrophysics Data System (ADS)

Dugar, Sumit; Smith, Paul; Parajuli, Binod; Khanal, Sonu; Brown, Sarah; Gautam, Dilip; Bhandari, Dinanath; Gurung, Gehendra; Shakya, Puja; Kharbuja, RamGopal; Uprety, Madhab

2017-04-01

Operationalising effective Flood Early Warning Systems (EWS) in developing countries like Nepal poses numerous challenges, with complex topography and geology, sparse network of river and rainfall gauging stations and diverse socio-economic conditions. Despite these challenges, simple real-time monitoring based EWSs have been in place for the past decade. A key constraint of these simple systems is the very limited lead time for response - as little as 2-3 hours, especially for rivers originating from steep mountainous catchments. Efforts to increase lead time for early warning are focusing on imbedding forecasts into the existing early warning systems. In 2016, the Nepal Department of Hydrology and Meteorology (DHM) piloted an operational Probabilistic Flood Forecasting Model in major river basins across Nepal. This comprised a low data approach to forecast water levels, developed jointly through a research/practitioner partnership with Lancaster University and WaterNumbers (UK) and the International NGO Practical Action. Using Data-Based Mechanistic Modelling (DBM) techniques, the model assimilated rainfall and water levels to generate localised hourly flood predictions, which are presented as probabilistic forecasts, increasing lead times from 2-3 hours to 7-8 hours. The Nepal DHM has simultaneously started utilizing forecasts from the Global Flood Awareness System (GLoFAS) that provides streamflow predictions at the global scale based upon distributed hydrological simulations using numerical ensemble weather forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). The aforementioned global and local models have already affected the approach to early warning in Nepal, being operational during the 2016 monsoon in the West Rapti basin in Western Nepal. On 24 July 2016, GLoFAS hydrological forecasts for the West Rapti indicated a sharp rise in river discharge above 1500 m3/sec (equivalent to the river warning level at 5 meters) with 53% probability of exceeding the Medium Level Alert in two days. Rainfall stations upstream of the West Rapti catchment recorded heavy rainfall on 26 July, and localized forecasts from the probabilistic model at 8 am suggested that the water level would cross a pre-determined warning level in the next 3 hours. The Flood Forecasting Section at DHM issued a flood advisory, and disseminated SMS flood alerts to more than 13,000 at-risk people residing along the floodplains. Water levels crossed the danger threshold (5.4 meters) at 11 am, peaking at 8.15 meters at 10 pm. Extension of the warning lead time from probabilistic forecasts was significant in minimising the risk to lives and livelihoods as communities gained extra time to prepare, evacuate and respond. Likewise, longer timescale forecasts from GLoFAS could be potentially linked with no-regret early actions leading to improved preparedness and emergency response. These forecasting tools have contributed to enhance the effectiveness and efficiency of existing community based systems, increasing the lead time for response. Nevertheless, extensive work is required on appropriate ways to interpret and disseminate probabilistic forecasts having longer (2-14 days) and shorter (3-5 hours) time horizon for operational deployment as there are numerous uncertainties associated with predictions.

Improving Arctic Sea Ice Edge Forecasts by Assimilating High Horizontal Resolution Sea Ice Concentration Data into the US Navy’s Ice Forecast Systems

DTIC Science & Technology

2016-06-13

Global Ocean Forecast System 3.1 also showed a substantial improvement in ice edge location over a system using the SSMIS sea ice concentration product... Global Ocean Fore- cast System (GOFS 3.1). Prior to 2 February 2015, the ice concentration fields from both ACNFS and GOFS 3.1 had been updated with...Scanning Radiometer (AMSR2) on the Japan Aerospace Exploration Agency (JAXA) Global Change Observation Mission – Water (GCOM-W) platform became available

Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States.

PubMed

Yamana, Teresa K; Kandula, Sasikiran; Shaman, Jeffrey

2017-11-01

Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time.