The sensitivity to the microphysical schemes on the skill of forecasting the track and intensity of tropical cyclones using WRF-ARW model

NASA Astrophysics Data System (ADS)

Choudhury, Devanil; Das, Someshwar

2017-06-01

The Advanced Research WRF (ARW) model is used to simulate Very Severe Cyclonic Storms (VSCS) Hudhud (7-13 October, 2014), Phailin (8-14 October, 2013) and Lehar (24-29 November, 2013) to investigate the sensitivity to microphysical schemes on the skill of forecasting track and intensity of the tropical cyclones for high-resolution (9 and 3 km) 120-hr model integration. For cloud resolving grid scale (<5 km) cloud microphysics plays an important role. The performance of the Goddard, Thompson, LIN and NSSL schemes are evaluated and compared with observations and a CONTROL forecast. This study is aimed to investigate the sensitivity to microphysics on the track and intensity with explicitly resolved convection scheme. It shows that the Goddard one-moment bulk liquid-ice microphysical scheme provided the highest skill on the track whereas for intensity both Thompson and Goddard microphysical schemes perform better. The Thompson scheme indicates the highest skill in intensity at 48, 96 and 120 hr, whereas at 24 and 72 hr, the Goddard scheme provides the highest skill in intensity. It is known that higher resolution domain produces better intensity and structure of the cyclones and it is desirable to resolve the convection with sufficiently high resolution and with the use of explicit cloud physics. This study suggests that the Goddard cumulus ensemble microphysical scheme is suitable for high resolution ARW simulation for TC's track and intensity over the BoB. Although the present study is based on only three cyclones, it could be useful for planning real-time predictions using ARW modelling system.

Intermittent Demand Forecasting in a Tertiary Pediatric Intensive Care Unit.

PubMed

Cheng, Chen-Yang; Chiang, Kuo-Liang; Chen, Meng-Yin

2016-10-01

Forecasts of the demand for medical supplies both directly and indirectly affect the operating costs and the quality of the care provided by health care institutions. Specifically, overestimating demand induces an inventory surplus, whereas underestimating demand possibly compromises patient safety. Uncertainty in forecasting the consumption of medical supplies generates intermittent demand events. The intermittent demand patterns for medical supplies are generally classified as lumpy, erratic, smooth, and slow-moving demand. This study was conducted with the purpose of advancing a tertiary pediatric intensive care unit's efforts to achieve a high level of accuracy in its forecasting of the demand for medical supplies. On this point, several demand forecasting methods were compared in terms of the forecast accuracy of each. The results confirm that applying Croston's method combined with a single exponential smoothing method yields the most accurate results for forecasting lumpy, erratic, and slow-moving demand, whereas the Simple Moving Average (SMA) method is the most suitable for forecasting smooth demand. In addition, when the classification of demand consumption patterns were combined with the demand forecasting models, the forecasting errors were minimized, indicating that this classification framework can play a role in improving patient safety and reducing inventory management costs in health care institutions.

Hurricane Intensity Forecasts with a Global Mesoscale Model on the NASA Columbia Supercomputer

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Atlas, Robert

2006-01-01

It is known that General Circulation Models (GCMs) have insufficient resolution to accurately simulate hurricane near-eye structure and intensity. The increasing capabilities of high-end computers (e.g., the NASA Columbia Supercomputer) have changed this. In 2004, the finite-volume General Circulation Model at a 1/4 degree resolution, doubling the resolution used by most of operational NWP center at that time, was implemented and run to obtain promising landfall predictions for major hurricanes (e.g., Charley, Frances, Ivan, and Jeanne). In 2005, we have successfully implemented the 1/8 degree version, and demonstrated its performance on intensity forecasts with hurricane Katrina (2005). It is found that the 1/8 degree model is capable of simulating the radius of maximum wind and near-eye wind structure, and thereby promising intensity forecasts. In this study, we will further evaluate the model s performance on intensity forecasts of hurricanes Ivan, Jeanne, Karl in 2004. Suggestions for further model development will be made in the end.

Forecasting intense geomagnetic activity using interplanetary magnetic field data

NASA Astrophysics Data System (ADS)

Saiz, E.; Cid, C.; Cerrato, Y.

2008-12-01

Southward interplanetary magnetic fields are considered traces of geoeffectiveness since they are a main agent of magnetic reconnection of solar wind and magnetosphere. The first part of this work revises the ability to forecast intense geomagnetic activity using different procedures available in the literature. The study shows that current methods do not succeed in making confident predictions. This fact led us to develop a new forecasting procedure, which provides trustworthy results in predicting large variations of Dst index over a sample of 10 years of observations and is based on the value Bz only. The proposed forecasting method appears as a worthy tool for space weather purposes because it is not affected by the lack of solar wind plasma data, which usually occurs during severe geomagnetic activity. Moreover, the results obtained guide us to provide a new interpretation of the physical mechanisms involved in the interaction between the solar wind and the magnetosphere using Faraday's law.

Assimilation of Tropical Cyclone Track and Wind Radius Data with an Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Kunii, M.

2014-12-01

Improving tropical cyclone (TC) forecasts is one of the most important issues in meteorology, but TC intensity forecasts are a challenging task. Because the lack of observations near TCs usually results in degraded accuracy of initial fields, utilizing TC advisory data in data assimilation typically has started with an ensemble Kalman filtering (EnKF). In this study, TC intensity and position information was directly assimilated using the EnKF, and the impact of these observations was investigated by comparing different assimilation strategies. Another experiment with TC wind radius data was carried out to examine the influence of TC shape parameters. Sensitivity experiments indicated that the assimilation of TC intensity and position data yielded results that were superior to those based on conventional assimilation of TC minimum sea level pressure as a standard surface pressure observation. Assimilation of TC radius data modified TC outer circulations closer to observations. The impacts of these TC parameters were also evaluated using the case of Typhoon Talas in 2011. The TC intensity, position, and wind radius data led to improved TC track forecasts and thence to improved precipitation forecasts. These results imply that initialization with these TC-related observations benefits TC forecasts, offering promise for the prevention and mitigation of natural disasters caused by TCs.

Relationships between total lightning, deep convection, and tropical cyclone intensity change

NASA Astrophysics Data System (ADS)

Xu, Weixin; Rutledge, Steven A.; Zhang, Wenjuan

2017-07-01

This study investigates the characteristics of total lightning in the inner core (INCO, 0-100 km) and outer rainband (OB, 200-400 km) of tropical cyclones (TC). Relationships between flash density (FLD), convective intensity, and TC intensity change are further examined. FLD shows a bimodal structure with a strong maximum in the eyewall (INCO, 0-50 km) and a secondary maximum in the OB. FLD maximizes under conditions of warmest sea surface temperature (SST) and large values of vertical wind shear. Compared to OB FLD, INCO FLD is less sensitive to SST increase but shows greater variability in relation to shear. Intensifying TCs have substantially lower INCO (but higher OB) FLD compared to weakening and neutral TCs. Similar trends are shown in radar quantities (volume of 30 dBZ echoes in the mixed phase). rapidly intensifying (RI) TCs also show significantly smaller FLD and VOL30 than slowly intensifying TCs, indicating the potential of these parameters in forecasting RI. INCO (OB) FLD decreases (increases) 12-18 h preceding the onset of RI, while INCO (OB) FLD increases (decreases) 6-12 h prior to TC weakening. These relationships between lightning and TC intensity change (+24 h) are generally maintained regardless of prior (-24 h) TC intensity change status. However, convective depth and vertically integrated ice content in the INCO increased preceding TC intensification, suggesting the lack of supercooled liquid content and establishment of glaciated conditions (evident by an increase in the 20 dBZ and decrease in the 30 dBZ echo volume) in the INCO of intensifying TCs, especially RI.

The Structure of Vertical Wind Shear in Tropical Cyclone Environments: Implications for Forecasting and Predictability

NASA Astrophysics Data System (ADS)

Finocchio, Peter M.

The vertical wind shear measured between 200 and 850 hPa is commonly used to diagnose environmental interactions with a tropical cyclone (TC) and to forecast the storm's intensity and structural evolution. More often than not, stronger vertical shear within this deep layer prohibits the intensification of TCs and leads to predictable asymmetries in precipitation. But such bulk measures of vertical wind shear can occasionally mislead the forecaster. In the first part of this dissertation, we use a series of idealized numerical simulations to examine how a TC responds to changing the structure of unidirectional vertical wind shear while fixing the 200-850-hPa shear magnitude. These simulations demonstrate a significant intensity response, in which shear concentrated in shallow layers of the lower troposphere prevents vortex intensification. We attribute the arrested development of TCs in lower-level shear to the intrusion of mid-level environmental air over the surface vortex early in the simulations. Convection developing on the downshear side of the storm interacts with the intruding air so as to enhance the downward flux of low-entropy air into the boundary layer. We also construct a two-dimensional intensity response surface from a set of simulations that sparsely sample the joint shear height-depth parameter space. This surface reveals regions of the two-parameter space for which TC intensity is particularly sensitive. We interpret these parameter ranges as those which lead to reduced intensity predictability. Despite the robust response to changing the shape of a sheared wind profile in idealized simulations, we do not encounter such sensitivity within a large set of reanalyzed TCs in the Northern Hemisphere. Instead, there is remarkable consistency in the structure of reanalyzed wind profiles around TCs. This is evident in the distributions of two new parameters describing the height and depth of vertical wind shear, which highlight a clear preference for

Effect of the Initial Vortex Size on Intensity Change in the WRF-ROMS Coupled Model

NASA Astrophysics Data System (ADS)

Zhao, Xiaohui; Chan, Johnny C. L.

2017-12-01

Numerous studies have demonstrated that the tropical cyclone (TC) induced sea surface temperature (SST) cooling strongly depends on the preexisting oceanic condition and TC characteristics. However, very few focused on the correlation of SST cooling and the subsequent intensity with TC size. Therefore, a series of idealized numerical experiments are conducted using the Weather Research Forecasting (WRF) model coupled with the Regional Ocean Model System (ROMS) model to understand how the vortex size is related to SST cooling and subsequent intensity changes of a stationary TC-like vortex. In the uncoupled experiments, the radius of maximum wind (RMW) and size (radius of gale-force wind (R17)) both depend on the initial size within the 72 h simulation. The initially small vortex is smaller than the medium and large vortices throughout its life cycle and is the weakest. In other words, thermodynamic processes do not contribute as much to the R17 change as the dynamic processes proposed (e.g., angular momentum transport) in previous studies. In the coupled experiments, the area-averaged SST cooling induced by medium and large TCs within the inner-core region is comparable due to the similar surface winds and thus mixing in the ocean. Although a stronger SST cooling averaged within a larger region outside the inner-core is induced by the larger TC, the intensity of the larger TC is more intense. This is because that the enthalpy flux in the inner-core region is higher in the larger TC than that in the medium and small TCs.

An effort to improve track and intensity prediction of tropical cyclones through vortex initialization in NCUM-global model

NASA Astrophysics Data System (ADS)

Singh, Vivek; Routray, A.; Mallick, Swapan; George, John P.; Rajagopal, E. N.

2016-05-01

Tropical cyclones (TCs) have strong impact on socio-economic conditions of the countries like India, Bangladesh and Myanmar owing to its awful devastating power. This brings in the need of precise forecasting system to predict the tracks and intensities of TCs accurately well in advance. However, it has been a great challenge for major operational meteorological centers over the years. Genesis of TCs over data sparse warm Tropical Ocean adds more difficulty to this. Weak and misplaced vortices at initial time are one of the prime sources of track and intensity errors in the Numerical Weather Prediction (NWP) models. Many previous studies have reported the forecast skill of track and intensity of TC improved due to the assimilation of satellite data along with vortex initialization (VI). Keeping this in mind, an attempt has been made to investigate the impact of vortex initialization for simulation of TC using UK-Met office global model, operational at NCMRWF (NCUM). This assessment is carried out by taking the case of a extremely severe cyclonic storm "Chapala" that occurred over Arabian Sea (AS) from 28th October to 3rd November 2015. Two numerical experiments viz. Vort-GTS (Assimilation of GTS observations with VI) and Vort-RAD (Same as Vort-GTS with assimilation of satellite data) are carried out. This vortex initialization study in NCUM model is first of its type over North Indian Ocean (NIO). The model simulation of TC is carried out with five different initial conditions through 24 hour cycles for both the experiments. The results indicate that the vortex initialization with assimilation of satellite data has a positive impact on the track and intensity forecast, landfall time and position error of the TCs.

Tropical cyclone intensity change. A quantitative forecasting scheme

NASA Technical Reports Server (NTRS)

Dropco, K. M.; Gray, W. M.

1981-01-01

One to two day future tropical cyclone intensity change from both a composite and an individual case point-of-view are discussed. Tropical cyclones occurring in the Gulf of Mexico during the period 1957-1977 form the primary data source. Weather charts of the NW Atlantic were initially examined, but few differences were found between intensifying and non-intensifying cyclones. A rawinsonde composite analysis detected composite differences in the 200 mb height fields, the 850 mb temperature fields, the 200 mb zonal wind and the vertical shears of the zonal wind. The individual cyclones which make up the composite study were then separately examined using this composite case knowledge. Similar parameter differences were found in a majority of individual cases. A cyclone intensity change forecast scheme was tested against independent storm cases. Correct predictions of intensification or non-intensification could be made approximately 75% of the time.

Interval forecasting of cyberattack intensity on informatization objects of industry using probability cluster model

NASA Astrophysics Data System (ADS)

Krakovsky, Y. M.; Luzgin, A. N.; Mikhailova, E. A.

2018-05-01

At present, cyber-security issues associated with the informatization objects of industry occupy one of the key niches in the state management system. As a result of functional disruption of these systems via cyberattacks, an emergency may arise related to loss of life, environmental disasters, major financial and economic damage, or disrupted activities of cities and settlements. When cyberattacks occur with high intensity, in these conditions there is the need to develop protection against them, based on machine learning methods. This paper examines interval forecasting and presents results with a pre-set intensity level. The interval forecasting is carried out based on a probabilistic cluster model. This method involves forecasting of one of the two predetermined intervals in which a future value of the indicator will be located; probability estimates are used for this purpose. A dividing bound of these intervals is determined by a calculation method based on statistical characteristics of the indicator. Source data are used that includes a number of hourly cyberattacks using a honeypot from March to September 2013.

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.

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

A new aircraft hurricane wind climatology and applications in assessing the predictive skill of tropical cyclone intensity using high-resolution ensemble forecasts

NASA Astrophysics Data System (ADS)

Judt, Falko; Chen, Shuyi S.

2015-07-01

Hurricane surface wind is a key measure of storm intensity. However, a climatology of hurricane winds is lacking to date, largely because hurricanes are relatively rare events and difficult to observe over the open ocean. Here we present a new hurricane wind climatology based on objective surface wind analyses, which are derived from Stepped Frequency Microwave Radiometer measurements acquired by NOAA WP-3D and U.S. Air Force WC-130J hurricane hunter aircraft. The wind data were collected during 72 aircraft reconnaissance missions into 21 western Atlantic hurricanes from 1998 to 2012. This climatology provides an opportunity to validate hurricane intensity forecasts beyond the simplistic maximum wind speed metric and allows evaluating the predictive skill of probabilistic hurricane intensity forecasts using high-resolution model ensembles. An example of application is presented here using a 1.3 km grid spacing Weather Research and Forecasting model ensemble forecast of Hurricane Earl (2010).

Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit

PubMed Central

Hoover, Stephen; Jackson, Eric V.; Paul, David; Locke, Robert

2016-01-01

Summary Background Accurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations. Objective Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasting models, (ii) explore models with and without patient data characteristics obtained at the time of admission, and (iii) evaluate accuracy of the models compared with the fixed average census approach. Methods We used five years of retrospective daily NICU census data for model development (January 2008 – December 2012, N=1827 observations) and one year of data for validation (January – December 2013, N=365 observations). Best-fitting models of ARIMA and linear regression were applied to various 7-day prediction periods and compared using error statistics. Results The census showed a slightly increasing linear trend. Best fitting models included a non-seasonal model, ARIMA(1,0,0), seasonal ARIMA models, ARIMA(1,0,0)x(1,1,2)7 and ARIMA(2,1,4)x(1,1,2)14, as well as a seasonal linear regression model. Proposed forecasting models resulted on average in 36.49% improvement in forecasting accuracy compared with the fixed average census approach. Conclusions Time series models provide higher prediction accuracy under different census conditions compared with the fixed average census approach. Presented methodology is easily applicable in clinical practice, can be generalized to other care settings, support short- and long-term census forecasting, and inform staff resource planning. PMID:27437040

Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit.

PubMed

Capan, Muge; Hoover, Stephen; Jackson, Eric V; Paul, David; Locke, Robert

2016-01-01

Accurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations. Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasting models, (ii) explore models with and without patient data characteristics obtained at the time of admission, and (iii) evaluate accuracy of the models compared with the fixed average census approach. We used five years of retrospective daily NICU census data for model development (January 2008 - December 2012, N=1827 observations) and one year of data for validation (January - December 2013, N=365 observations). Best-fitting models of ARIMA and linear regression were applied to various 7-day prediction periods and compared using error statistics. The census showed a slightly increasing linear trend. Best fitting models included a non-seasonal model, ARIMA(1,0,0), seasonal ARIMA models, ARIMA(1,0,0)x(1,1,2)7 and ARIMA(2,1,4)x(1,1,2)14, as well as a seasonal linear regression model. Proposed forecasting models resulted on average in 36.49% improvement in forecasting accuracy compared with the fixed average census approach. Time series models provide higher prediction accuracy under different census conditions compared with the fixed average census approach. Presented methodology is easily applicable in clinical practice, can be generalized to other care settings, support short- and long-term census forecasting, and inform staff resource planning.

Impact on Hurricane Track and Intensity Forecasts of GPS Dropwindsonde Observations from the First-Season Flights of the NOAA Gulfstream-IV Jet Aircraft.

NASA Astrophysics Data System (ADS)

Aberson, Sim D.; Franklin, James L.

1999-03-01

In 1997, the Tropical Prediction Center (TPC) began operational Gulfstream-IV jet aircraft missions to improve the numerical guidance for hurricanes threatening the continental United States, Puerto Rico, and the Virgin Islands. During these missions, the new generation of Global Positioning System dropwindsondes were released from the aircraft at 150-200-km intervals along the flight track in the environment of the tropical cyclone to obtain profiles of wind, temperature, and humidity from flight level to the surface. The observations were ingested into the global model at the National Centers for Environmental Prediction, which subsequently serves as initial and boundary conditions to other numerical tropical cyclone models. Because of a lack of tropical cyclone activity in the Atlantic basin, only five such missions were conducted during the inaugural 1997 hurricane season.Due to logistical constraints, sampling in all quadrants of the storm environment was accomplished in only one of the five cases during 1997. Nonetheless, the dropwindsonde observations improved mean track forecasts from the Geophysical Fluid Dynamics Laboratory hurricane model by as much as 32%, and the intensity forecasts by as much as 20% during the hurricane watch period (within 48 h of projected landfall). Forecasts from another dynamical tropical cyclone model (VICBAR) also showed modest improvements with the dropwindsonde observations. These improvements, if confirmed by a larger sample, represent a large step toward the forecast accuracy goals of TPC. The forecast track improvements are as large as those accumulated over the past 20-25 years, and those for forecast intensity provide further evidence that better synoptic-scale data can lead to more skillful dynamical tropical cyclone intensity forecasts.

Short-term acoustic forecasting via artificial neural networks for neonatal intensive care units.

PubMed

Young, Jason; Macke, Christopher J; Tsoukalas, Lefteri H

2012-11-01

Noise levels in hospitals, especially neonatal intensive care units (NICUs), have become of great concern for hospital designers. This paper details an artificial neural network (ANN) approach to forecasting the sound loads in NICUs. The ANN is used to learn the relationship between past, present, and future noise levels. By training the ANN with data specific to the location and device used to measure the sound, the ANN is able to produce reasonable predictions of noise levels in the NICU. Best case results show average absolute errors of 5.06 ± 4.04% when used to predict the noise levels one hour ahead, which correspond to 2.53 dBA ± 2.02 dBA. The ANN has the tendency to overpredict during periods of stability and underpredict during large transients. This forecasting algorithm could be of use in any application where prediction and prevention of harmful noise levels are of the utmost concern.

Forecasts of land uses

Treesearch

David N. Wear

2013-01-01

Key FindingsBetween 30 million and 43 million acres of land in the South are forecasted to be developed for urban uses by 2060 from a base of 30 million acres in 1997. These forecasts are based on a continuation of historical development intensities.From 1997 to 2060, the South is forecasted to lose between 11 million acres (7...

Enhanced Ahead-of-Eye TC Coastal Ocean Cooling Processes and their Impact on Air-Sea Heat Fluxes and Storm Intensity

NASA Astrophysics Data System (ADS)

Seroka, G. N.; Miles, T. N.; Glenn, S. M.; Xu, Y.; Forney, R.; Roarty, H.; Schofield, O.; Kohut, J. T.

2016-02-01

Any landfalling tropical cyclone (TC) must first traverse the coastal ocean. TC research, however, has focused over the deep ocean, where TCs typically spend the vast majority of their lifetime. This paper will show that the ocean's response to TCs can be different between deep and shallow water, and that the additional shallow water processes must be included in coupled models for accurate air-sea flux treatment and TC intensity prediction. The authors will present newly observed coastal ocean processes that occurred in response to Hurricane Irene (2011), due to the presence of a coastline, an ocean bottom, and highly stratified conditions. These newly observed processes led to enhanced ahead-of-eye SST cooling that significantly impacted air-sea heat fluxes and Irene's operationally over-predicted storm intensity. Using semi-idealized modeling, we find that in shallow water in Irene, only 6% of cooling due to air-sea heat fluxes, 17% of cooling due to 1D vertical mixing, and 50% of cooling due to all processes (1D mixing, air-sea heat fluxes, upwelling, and advection) occurred ahead-of-eye—consistent with previous studies. Observations from an underwater glider and buoys, however, indicated 75-100% of total SST cooling over the continental shelf was ahead-of-eye. Thus, the new coastal ocean cooling processes found in this study must occur almost completely ahead-of-eye. We show that Irene's intense cooling was not captured by basic satellite SST products and coupled ocean-atmosphere hurricane models, and that including the cooling in WRF modeling mitigated the high bias in model predictions. Finally, we provide evidence that this SST cooling—not track, wind shear, or dry air intrusion—was the key missing contribution to Irene's decay just prior to NJ landfall. Ongoing work is exploring the use of coupled WRF-ROMS modeling in the coastal zone.

The relationships between precipitation, convective cloud and tropical cyclone intensity change

NASA Astrophysics Data System (ADS)

Ruan, Z.; Wu, Q.

2017-12-01

Using 16 years precipitation, brightness temperature (IR BT) data and tropical cyclone (TC) information, this study explores the relationship between precipitation, convective cloud and tropical cyclone (TC) intensity change in the Western North Pacific Ocean. It is found that TC intensity has positive relation with TC precipitation. TC precipitation increases with increased TC intensity. Based on the different phase of diurnal cycle, convective TC clouds were divided into very cold deep convective clouds (IR BTs<208K) and cold high clouds (208K

Hydrometeor Trajectories and Distributions in a Simulation of TC Rapid Intensification (RI)

NASA Astrophysics Data System (ADS)

Zhu, Z.; Zhu, P.

2010-12-01

It has long been recognized that the microphysics scheme used in a numerical simulation of tropical cyclones (TC) can greatly affect the precipitation distribution, intensity and thermodynamic structure of the simulated TC. This suggests that the mixing ratios, concentrations and size distributions of hydrometeor(snow, graupel,rain,cloud ice) are important factors in the evolution of TC . The transport of hydrometeor may have a strong influence on these factors through its interactions with the growth and the latent heat forcing of hydrometeor and the wind filed, hence is a key to understanding TC microphysics. Schematic hydrometeor trajectories were first constructed using 3-D wind field and particle fallspeeds derived from airborne radar observations in a steady-state mature hurricane,Alicia(1983). Since then, little effort has been put in understanding hydrometeor transport in TC, especially the potential link between its evolution and the intensity and structure changes in a non-steady-state TC. This study is focused on investigating such a link by means of numerical simulations of TC Rapid Intensification(RI) using WRF model. We use the tracer utility in WRF to construct hydrometeor trajectories. Most of the popular microphysics schemes are tested, and the most reasonable test( which is determined by comparing the simulated TC intensity and structure with airborne radar observations) and the ensemble mean of all the tests are picked for detailed examinations.

A similarity retrieval approach for weighted track and ambient field of tropical cyclones

NASA Astrophysics Data System (ADS)

Li, Ying; Xu, Luan; Hu, Bo; Li, Yuejun

2018-03-01

Retrieving historical tropical cyclones (TC) which have similar position and hazard intensity to the objective TC is an important means in TC track forecast and TC disaster assessment. A new similarity retrieval scheme is put forward based on historical TC track data and ambient field data, including ERA-Interim reanalysis and GFS and EC-fine forecast. It takes account of both TC track similarity and ambient field similarity, and optimal weight combination is explored subsequently. Result shows that both the distance and direction errors of TC track forecast at 24-hour timescale follow an approximately U-shape distribution. They tend to be large when the weight assigned to track similarity is close to 0 or 1.0, while relatively small when track similarity weight is from 0.2˜0.7 for distance error and 0.3˜0.6 for direction error.

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in

Precipitation, Convective Clouds, and Their Connections With Tropical Cyclone Intensity and Intensity Change

NASA Astrophysics Data System (ADS)

Ruan, Zhenxin; Wu, Qiaoyan

2018-01-01

In this paper, satellite-based precipitation, clouds with infrared (IR) brightness temperature (BT), and tropical cyclone (TC) data from 2000 to 2015 are used to explore the relationship between precipitation, convective cloud, and TC intensity change in the Western North Pacific Ocean. An IR BT of 208 K was chosen as a threshold for deep convection based on different diurnal cycles of IR BT. More precipitation and colder clouds with 208 K < IR BT < 240 K are found as storms intensify, while TC 24 h future intensity change is closely connected with very deep convective clouds with IR BT < 208 K. Intensifying TCs follow the occurrence of colder clouds with IR BT < 208 K with greater areal extents. As an indicator of very deep convective clouds, IR BT < 208 K is suggested to be a good predictor of TC intensity change. Based upon the 16 year analysis in the western North Pacific, TCs under the conditions that the mean temperature of very deep convective clouds is less than 201 K, and the coverage of this type of clouds is more than 27.4% within a radius of 300 km of the TC center, will more likely undergo rapid intensification after 24 h.

Leveraging LSTM for rapid intensifications prediction of tropical cyclones

NASA Astrophysics Data System (ADS)

Li, Y.; Yang, R.; Yang, C.; Yu, M.; Hu, F.; Jiang, Y.

2017-10-01

Tropical cyclones (TCs) usually cause severe damages and destructions. TC intensity forecasting helps people prepare for the extreme weather and could save lives and properties. Rapid Intensifications (RI) of TCs are the major error sources of TC intensity forecasting. A large number of factors, such as sea surface temperature and wind shear, affect the RI processes of TCs. Quite a lot of work have been done to identify the combination of conditions most favorable to RI. In this study, deep learning method is utilized to combine conditions for RI prediction of TCs. Experiments show that the long short-term memory (LSTM) network provides the ability to leverage past conditions to predict TC rapid intensifications.

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

46 CFR 161.013-5 - Intensity requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of the light corrected for the length of the flash and is determined by the formula: EFI = I × (tc − ti) / 0.2 + (tc − ti) Where: I is the measured intensity of the fixed beam, tc is the contact closure...

46 CFR 161.013-5 - Intensity requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... of the light corrected for the length of the flash and is determined by the formula: EFI = I × (tc − ti) / 0.2 + (tc − ti) Where: I is the measured intensity of the fixed beam, tc is the contact closure...

The use of ambient humidity conditions to improve influenza forecast.

PubMed

Shaman, Jeffrey; Kandula, Sasikiran; Yang, Wan; Karspeck, Alicia

2017-11-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

Experiments with Tropical Cyclone Wave and Intensity Forecasts

DTIC Science & Technology

2008-09-30

algorithm In collaboration with Paul Wittmann (Fleet Numerical Metorology and Oceanography Center) and Hendrik Tolman (National Centers for...Wittmann, P.A., C Sampson and H. Tolman: 2006: Wave Analysis Guidance for Tropical Cyclone Forecast Advisories. 9th International Workshop on Wave

Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7): experimental design and preliminary results

NASA Astrophysics Data System (ADS)

Nakano, Masuo; Wada, Akiyoshi; Sawada, Masahiro; Yoshimura, Hiromasa; Onishi, Ryo; Kawahara, Shintaro; Sasaki, Wataru; Nasuno, Tomoe; Yamaguchi, Munehiko; Iriguchi, Takeshi; Sugi, Masato; Takeuchi, Yoshiaki

2017-03-01

Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ˜ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is

Impact of global warming on the typhoon intensities during 2015

NASA Astrophysics Data System (ADS)

Kang, N. Y.; Yang, S. H.; Elsner, J.; Chun, Y.

2017-12-01

The climate of 2015 was characterized by a strong El Nino, global warmth, and record setting tropical cyclone (TC) intensity for western North Pacific typhoons. In this study, the highest TC intensity in 32 years (1984-2015) is shown to be a consequence of above normal TC activity—following natural internal variation—and greater efficiency of intensity. The efficiency of intensity (EINT) is termed the `blasting effect' and refers to typhoon intensification at the expense of occurrence. Statistical models show that the EINT is mostly due to the anomalous warmth in the environment as indicated by global mean sea-surface temperature. In comparison, the EINT due to El Nino is negligibly small. This implies that the record-setting intensity of 2015 might not have occurred without environmental warming and suggests that a year with even greater TC intensity is possible in the near future when above normal activity coincides with another record EINT due to continuous warming.

The use of ambient humidity conditions to improve influenza forecast

PubMed Central

Kandula, Sasikiran; Karspeck, Alicia

2017-01-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1–4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast. PMID:29145389

The Impact of Lightning on Hurricane Rapid Intensification Forecasts Using the HWRF Model

NASA Astrophysics Data System (ADS)

Rosado, K.; Tallapragada, V.; Jenkins, G. S.

2016-12-01

In 2010, the National Oceanic and Atmospheric Administration (NOAA) created the Hurricane Forecast Improvement Project (HFIP) with the main goal of improving the tropical cyclone intensity and track forecasts by 50% in ten years. One of the focus areas is the improvement of the tropical cyclone rapid intensification (RI) forecasts. In order to contribute to this task, the role of lightning during the life cycle of a tropical cyclone using the NCEP operational HWRF hurricane model has been investigated. We ask two key research questions: (1) What is the functional relationship between atmospheric moisture content, lightning, and intensity in the HWRF model? and (2) How well does the HWRF model forecast the spatial distributions of lightning before, during, and after tropical cyclone intensification, especially for RI events? In order to address those questions, a lightning parameterization scheme called the Lightning Potential Index (LPI) was implemented into the HWRF model. The selected study cases to test the LPI implementation on the 2015 HWRF (operational version) are: Earl and Joaquin (North Atlantic), Haiyan (Western North Pacific), and Patricia (Eastern North Pacific). Five-day forecasts was executed on each case study with emphasis on rapid intensification periods. An extensive analysis between observed "best track" intensity, model intensity forecast, and potential for lightning forecast was performed. Preliminary results show that: (1) strong correlation between lightning and intensity changes does exists; and (2) the potential for lightning increases to its maximum peak a few hours prior to the peak intensity of the tropical cyclone. LPI peak values could potentially serve as indicator for future rapid intensification periods. Results from this investigation are giving us a better understanding of the mechanism behind lightning as a proxy for tropical cyclone steady state intensification and tropical cyclone rapid intensification processes. Improvement of

Adaptive use of research aircraft data sets for hurricane forecasts

NASA Astrophysics Data System (ADS)

Biswas, M. K.; Krishnamurti, T. N.

2008-02-01

This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution.

ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

NASA Astrophysics Data System (ADS)

Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin

2016-11-01

In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

Tropical cyclones-Pacific Asian Research Campaign for Improvement of Intensity estimations/forecasts (T-PARCII): A research plan of typhoon aircraft observations in Japan

NASA Astrophysics Data System (ADS)

Tsuboki, Kazuhisa

2017-04-01

Typhoons are the most devastating weather system occurring in the western North Pacific and the South China Sea. Violent wind and heavy rainfall associated with a typhoon cause huge disaster in East Asia including Japan. In 2013, Supertyphoon Haiyan struck the Philippines caused a very high storm surge and more than 7000 people were killed. In 2015, two typhoons approached the main islands of Japan and severe flood occurred in the northern Kanto region. Typhoons are still the largest cause of natural disaster in East Asia. Moreover, many researches have projected increase of typhoon intensity with the climate change. This suggests that a typhoon risk is increasing in East Asia. However, the historical data of typhoon include large uncertainty. In particular, intensity data of the most intense typhoon category have larger error after the US aircraft reconnaissance of typhoon was terminated in 1987.The main objective of the present study is improvements of typhoon intensity estimations and of forecasts of intensity and track. We will perform aircraft observation of typhoon and the observed data are assimilated to numerical models to improve intensity estimation. Using radars and balloons, observations of thermodynamical and cloud-microphysical processes of typhoons will be also performed to improve physical processes of numerical model. In typhoon seasons (mostly in August and September), we will perform aircraft observations of typhoons. Using dropsondes from the aircraft, temperature, humidity, pressure, and wind are measured in surroundings of the typhoon inner core region. The dropsonde data are assimilated to a cloud-resolving model which has been developed in Nagoya University and named the Cloud Resolving Storm Simulator (CReSS). Then, more accurate estimations and forecasts of the typhoon intensity will be made as well as typhoon tracks. Furthermore, we will utilize a ground-based balloon with microscope camera, X-band precipitation radar, Ka-band cloud radar

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

Comparison of Dst Forecast Models for Intense Geomagnetic Storms

NASA Technical Reports Server (NTRS)

Ji, Eun-Young; Moon, Y.-J.; Gopalswamy, N.; Lee, D.-H.

2012-01-01

We have compared six disturbance storm time (Dst) forecast models using 63 intense geomagnetic storms (Dst <=100 nT) that occurred from 1998 to 2006. For comparison, we estimated linear correlation coefficients and RMS errors between the observed Dst data and the predicted Dst during the geomagnetic storm period as well as the difference of the value of minimum Dst (Delta Dst(sub min)) and the difference in the absolute value of Dst minimum time (Delta t(sub Dst)) between the observed and the predicted. As a result, we found that the model by Temerin and Li gives the best prediction for all parameters when all 63 events are considered. The model gives the average values: the linear correlation coefficient of 0.94, the RMS error of 14.8 nT, the Delta Dst(sub min) of 7.7 nT, and the absolute value of Delta t(sub Dst) of 1.5 hour. For further comparison, we classified the storm events into two groups according to the magnitude of Dst. We found that the model of Temerin and Lee is better than the other models for the events having 100 <= Dst < 200 nT, and three recent models (the model of Wang et al., the model of Temerin and Li, and the model of Boynton et al.) are better than the other three models for the events having Dst <= 200 nT.

Thermal Expansion Behavior in TcO2. Toward Breaking the Tc-Tc Bond.

PubMed

Reynolds, Emily; Zhang, Zhaoming; Avdeev, Maxim; Thorogood, Gordon J; Poineau, Frederic; Czerwinski, Kenneth R; Kimpton, Justin A; Kennedy, Brendan J

2017-08-07

The structure of TcO 2 between 25 and 1000 °C has been determined in situ using X-ray powder diffraction methods and is found to remain monoclinic in space group P2 1 /c. Thermal expansion in TcO 2 is highly anisotropic, with negative thermal expansion of the b axis observed above 700 °C. This is the result of an anomalous expansion along the a axis that is a consequence of weakening of the Tc-Tc bonds.

Influence of global warming on western North Pacific tropical cyclone intensities during 2015

NASA Astrophysics Data System (ADS)

Kang, Nam-Young; Yang, Se-Hwan; Elsner, James

2017-04-01

The climate of 2015 was characterized by a strong El Niño, global warmth, and record-setting tropical cyclone (TC) intensity for western North Pacific typhoons. In this study, the highest TC intensity in 32 years (1984-2015) is shown to be a consequence of above normal TC activity—following natural internal variation—and greater efficiency of intensity. The efficiency of intensity (EINT) is termed the 'blasting' effect and refers to typhoon intensification at the expense of occurrence. Statistical models show that the EINT is mostly due to the anomalous warmth in the environment as indicated by global mean sea-surface temperature. In comparison, the EINT due to El Niño is negligible. This implies that the record-setting intensity of 2015 might not have occurred without environmental warming and suggests that a year with even greater TC intensity is possible in the near future when above normal activity coincides with another record EINT due to continuous warming.

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.

[Transfer of allogeneic stem cell transplant recipients to the intensive care unit: Guidelines from the Francophone society of marrow transplantation and cellular therapy (SFGM-TC)].

PubMed

Moreau, Anne-Sophie; Bourhis, Jean-Henri; Contentin, Nathalie; Couturier, Marie-Anne; Delage, Jeremy; Dumesnil, Cécile; Gandemer, Virginie; Hichri, Yosr; Jost, Edgar; Platon, Laura; Jourdain, Mercé; Pène, Frédéric; Yakoub-Agha, Ibrahim

2016-11-01

Transferring a patient undergoing an allogeneic stem cell transplantation to the intensive care unit (ICU) is always a challenging situation on a medical and psychological point of view for the patient and his relatives as well as for the medical staff. Despite the progress in hematology and intensive care during the last decade, the prognosis of these patients admitted to the ICU remains poor and mortality is around 50 %. The harmonization working party of the SFGM-TC assembled hematologists and intensive care specialist in order to improve conditions and modalities of the transfer of a patient after allogeneic stem cell transplantation to the ICU. We propose a structured medical form comprising all essential information necessary for optimal medical care on ICU. Copyright © 2016. Published by Elsevier Masson SAS.

Investigating the sensitivity of hurricane intensity and trajectory to sea surface temperatures using the regional model WRF

NASA Astrophysics Data System (ADS)

Kilic, Cevahir; Raible, Christoph C.

2015-04-01

It is well known that the sea surface temperature (SST) has an influence on the development and intensification of tropical cyclones (TCs). This influence has become even more important during the past decades, as TCs show an intensification, which goes along with an increase in SSTs. The influence of sea surface temperature (SST) anomalies on the hurricane characteristics are investigated in a set of sensitivity experiments employing the Weather Research and Forecasting (WRF) model. The idealised experiments are performed for the case of Hurricane Katrina in 2005. (Kilic and Raible, 2013) The first set of sensitivity experiments with basin-wide changes of the SST magnitude shows that the intensity goes along with changes in the SST, i.e., an increase in SST leads to an intensification of Katrina. Additionally, the trajectory is shifted to the west (east), with increasing (decreasing) SSTs. The main reason is a strengthening of the background flow. To gain further insights in the dynamics, the potential vorticity (PV) and its tendency (PVT) are analysed. A positive PVT is located to the moving direction relative to the TC centre. Splitting the PVT in the horizontal advection, vertical advection, and diabatic heating terms, we find that mainly the horizontal advection term contributes to this PVT maximum, due to a steering by strong environmental flow. The impact of the diabatic heating is of minor importance and, hence, the TC motion is dominated by horizontal advection. The amount of the horizontal advection as well as the amount of the diabatic heating rise with increasing SST due to the enhanced Carnot cycle. The second set of experiments investigates the influence of Loop Current eddies idealised by localised SST anomalies. The intensity of Hurricane Katrina is enhanced with increasing SSTs close to the core of a TC. Negative nearby SST anomalies reduce the intensity. The trajectory only changes if positive SST anomalies are located west or north of the

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 MST radar technique: Requirements for operational weather forecasting

NASA Technical Reports Server (NTRS)

Larsen, M. F.

1983-01-01

There is a feeling that the accuracy of mesoscale forecasts for spatial scales of less than 1000 km and time scales of less than 12 hours can be improved significantly if resources are applied to the problem in an intensive effort over the next decade. Since the most dangerous and damaging types of weather occur at these scales, there are major advantages to be gained if such a program is successful. The interest in improving short term forecasting is evident. The technology at the present time is sufficiently developed, both in terms of new observing systems and the computing power to handle the observations, to warrant an intensive effort to improve stormscale forecasting. An assessment of the extent to which the so-called MST radar technique fulfills the requirements for an operational mesoscale observing network is reviewed and the extent to which improvements in various types of forecasting could be expected if such a network is put into operation are delineated.

Forecasting probabilistic seismic shaking for greater Tokyo from 400 years of intensity observations

USGS Publications Warehouse

Bozkurt, S.B.; Stein, R.S.; Toda, S.

2007-01-01

The long recorded history of earthquakes in Japan affords an opportunity to forecast seismic shaking exclusively from past shaking. We calculate the time-averaged (Poisson) probability of severe shaking by using more than 10,000 intensity observations recorded since AD 1600 in a 350 km-wide box centered on Tokyo. Unlike other hazard-assessment methods, source and site effects are included without modeling, and we do not need to know the size or location of any earthquake nor the location and slip rate of any fault. The two key assumptions are that the slope of the observed frequency-intensity relation at every site is the same, and that the 400-year record is long enough to encompass the full range of seismic behavior. Tests we conduct here suggest that both assumptions are sound. The resulting 30-year probability of IJMA ??? 6 shaking (??? PGA ??? 0.4 g or MMI ??? IX) is 30%-40% in Tokyo, Kawasaki, and Yokohama, and 10% 15% in Chiba and Tsukuba. This result means that there is a 30% chance that 4 million people will be subjected to IJMA ??? 6 shaking during an average 30-year period. We also produce exceedance maps of PGA for building-code regulations, and calculate short-term hazard associated with a hypothetical catastrophe bond. Our results resemble an independent assessment developed from conventional seismic hazard analysis for greater Tokyo. ?? 2007, Earthquake Engineering Research Institute.

Enhanced 99 Tc retention in glass waste form using Tc(IV)-incorporated Fe minerals

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

Um, Wooyong; Luksic, Steven A.; Wang, Guohui

Technetium (99Tc) immobilization by doping into iron oxide mineral phases may alleviate the problems with Tc volatility during vitrification of nuclear waste. Reduced Tc, Tc(IV), substitutes for Fe(III) in the crystal structure by a process of Tc reduction from Tc(VII) to Tc(IV) followed by co-precipitation of Fe oxide minerals. Two Tc-incorporated Fe minerals (Tc-goethite and Tc-magnetite/maghemite) were prepared and tested for Tc retention in glass melt samples at temperatures between 600 – 1,000 oC. After being cooled, the solid glass specimens prepared at different temperatures were analyzed for Tc oxidation state using Tc K-edge XANES. In most samples, Tc wasmore » partially oxidized from Tc(IV) to Tc(VII) as the melt temperature increased. However, Tc retention in glass melt samples prepared using Tc-incorporated Fe minerals were moderately higher than in glass prepared using KTcO4 because of limited and delayed Tc volatilization.« less

Using Deep Learning for Tropical Cyclone Intensity Estimation

NASA Astrophysics Data System (ADS)

Miller, J.; Maskey, M.; Berendes, T.

2017-12-01

Satellite-based techniques are the primary approach to estimating tropical cyclone (TC) intensity. Tropical cyclone warning centers worldwide still apply variants of the Dvorak technique for such estimations that include visual inspection of the satellite images. The National Hurricane Center (NHC) estimates about 10-20% uncertainty in its post analyses when only satellite-based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to TC intensity. With the ever-increasing quality and quantity of satellite observations of TCs, deep learning techniques designed to excel at pattern recognition have become more relevant in this area of study. In our current study, we aim to provide a fully objective approach to TC intensity estimation by utilizing deep learning in the form of a convolutional neural network trained to predict TC intensity (maximum sustained wind speed) using IR satellite imagery. Large amounts of training data are needed to train a convolutional neural network, so we use GOES IR images from historical tropical storms from the Atlantic and Pacific basins spanning years 2000 to 2015. Images are labeled using a special subset of the HURDAT2 dataset restricted to time periods with airborne reconnaissance data available in order to improve the quality of the HURDAT2 data. Results and the advantages of this technique are to be discussed.

HAKOU v3: SWIMS Hurricane Inundation Fast Forecasting Tool for Hawaii

DTIC Science & Technology

2012-02-01

SUBTITLE HAKOU v3: SWIMS Hurricane Inundation Fast Forecasting Tool For Hawaii 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Coupled SWAN+ADCIRC were driven with wind and pressure fields generated by the planetary boundary layer model TC96 (Thompson and Cardone 1996...F., and V. J. Cardone . 1996. Practical modeling of hurricane surface wind fields. J. Waterw. Port C-ASCE. 122(4): 195-205. Zijlema, M. 2010

Forecasting Frost Damage: Follow the Water

NASA Astrophysics Data System (ADS)

Rempel, A. W.

2015-12-01

Frost damage takes place when the pressure exerted against pore walls exceeds the cohesive strength of water-infiltrated rock and causes cracks to extend. Elegant theoretical treatments supported by meticulous field and laboratory observations have combined to unravel the basic mechanical and thermodynamic controls in idealized systems. Frost damage is most vigorous when conditions are cold enough that the net pressure exerted against the pore walls can cause crack extension, yet warm enough to enable the flow that supplies further ice growth in the newly opened space. This insight is applied here to develop practical geomorphic process laws for the effects of frost damage at the larger scales that are relevant for describing the evolution of landscapes. To this end, a direct connection is made between the intensity of frost damage and the porosity increase that results from gradients in water flux under conditions that are cold enough for ice-rock interactions to propagate cracks. This implies that the annual temperature variation at the ground surface can be combined with considerations of heat and mass transport to derive rigorous forecasts of the potential for frost damage that are tied to the increases in water mass that accompany solidification in porous rock. As an example, the image shows the depth-integrated porosity change λ promoted by crack growth at temperatures colder than -ΔTc over an annual cycle for different choices of mean annual temperature MAT and surface amplitude A (assuming a thermal diffusivity of 1 mm2/s and a power-law relationship between permeability and undercooling with exponent α=4, such that a base value of 10-14m2 is reached at a reference undercooling of 0.1 ºC). The abrupt onset in cracking once MAT decreases below a threshold is produced by the requirement that undercooling surpass ΔTc in order to generate sufficient pressures to propagate cracks. The eventual reduction and gradual tail in λ at colder MAT is produced by

Decision Theory: Individual Biases and Their Effect on Forecasting in an Organization.

DTIC Science & Technology

1983-12-01

has not bien a great deal written about how these biases effact decisicns in an organizational environment . The purpcse of -:his thesis is tc examine...and prospers while using fallible information to infer the stateb of his uncer- tain environment and to pr.dict future events. Experiments that have...chapters deal with data from two separate crganizati-ons in two different environments . The Judgmental processes of forecasTing future organizational

Enhanced 99Tc retention in glass waste form using Tc(IV)-incorporated Fe minerals

DOE PAGES

Um, Wooyong; Luksic, Steven A.; Wang, Guohui; ...

2017-09-07

We present that technetium ( 99Tc) immobilization by doping into iron oxide mineral phases may alleviate the problems with Tc volatility during vitrification of nuclear waste. Because reduced Tc, Tc(IV), substitutes for Fe(III) in the crystal structure by a process of Tc reduction from Tc(VII) to Tc(IV) followed by co-precipitation of Fe oxide minerals, two Tc-incorporated Fe minerals (Tc-goethite and Tc-magnetite/maghemite) were prepared and tested for Tc retention in glass melt samples at temperatures between 600 and 1000 °C. After being cooled, the solid glass specimens prepared at different temperatures at 600, 800, and 1000 °C were analyzed for Tcmore » oxidation state using Tc K-edge XANES. In most samples, Tc was partially (<60%) oxidized from Tc(IV) to Tc(VII) as the melt temperature increased up to 600 °C. However, most of Tc(IV) was completely (>95%) oxidized to Tc(VII) at temperature above 800 °C. Tc retention in glass melt samples prepared using Tc-incorporated Fe minerals were slightly higher (~10%) than in glass prepared using KTcO4 because of limited and delayed Tc volatilization.« less

Enhanced 99Tc retention in glass waste form using Tc(IV)-incorporated Fe minerals

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

Um, Wooyong; Luksic, Steven A.; Wang, Guohui

We present that technetium ( 99Tc) immobilization by doping into iron oxide mineral phases may alleviate the problems with Tc volatility during vitrification of nuclear waste. Because reduced Tc, Tc(IV), substitutes for Fe(III) in the crystal structure by a process of Tc reduction from Tc(VII) to Tc(IV) followed by co-precipitation of Fe oxide minerals, two Tc-incorporated Fe minerals (Tc-goethite and Tc-magnetite/maghemite) were prepared and tested for Tc retention in glass melt samples at temperatures between 600 and 1000 °C. After being cooled, the solid glass specimens prepared at different temperatures at 600, 800, and 1000 °C were analyzed for Tcmore » oxidation state using Tc K-edge XANES. In most samples, Tc was partially (<60%) oxidized from Tc(IV) to Tc(VII) as the melt temperature increased up to 600 °C. However, most of Tc(IV) was completely (>95%) oxidized to Tc(VII) at temperature above 800 °C. Tc retention in glass melt samples prepared using Tc-incorporated Fe minerals were slightly higher (~10%) than in glass prepared using KTcO4 because of limited and delayed Tc volatilization.« less

Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts

NASA Astrophysics Data System (ADS)

Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

2012-12-01

NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss

Increase in the Intensity of Postmonsoon Bay of Bengal Tropical Cyclones

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

Balaguru, Karthik; Taraphdar, Sourav; Leung, Lai-Yung R.

2014-05-28

The post-monsoon (October-November) tropical cyclone (TC) season in the Bay of Bengal has spawned many of the deadliest storms in recorded history. Here it is shown that the intensity of post-monsoon Bay of Bengal TCs, and the contribution of major TCs to total TC power, increased during 1981-2010. It is found that changes in environmental parameters are responsible for the observed increases in TC intensity. Increases in sea surface temperature and upper ocean heat content made the ocean more conducive to TC development, while enhanced convective instability made the atmosphere more favorable for the growth of TCs. The largest changesmore » in the atmosphere and ocean occurred in the eastern Bay of Bengal, where nearly all major TCs form. These changes are part of positive linear trends, suggesting that the intensity of post-monsoon Bay of Bengal TCs may continue to increase in the future.« less

TcCYPR04, a Cacao Papain-Like Cysteine-Protease Detected in Senescent and Necrotic Tissues Interacts with a Cystatin TcCYS4

PubMed Central

Cardoso, Thyago Hermylly Santana; Freitas, Ana Camila Oliveira; Andrade, Bruno Silva; de Sousa, Aurizangela Oliveira; Santiago, André da Silva; Koop, Daniela Martins; Gramacho, Karina Peres; Alvim, Fátima Cerqueira; Micheli, Fabienne; Pirovani, Carlos Priminho

2015-01-01

The interaction amongst papain-like cysteine-proteases (PLCP) and their substrates and inhibitors, such as cystatins, can be perceived as part of the molecular battlefield in plant-pathogen interaction. In cacao, four cystatins were identified and characterized by our group. We identified 448 proteases in cacao genome, whereof 134 were cysteine-proteases. We expressed in Escherichia coli a PLCP from cacao, named TcCYSPR04. Immunoblottings with anti-TcCYSPR04 exhibited protein increases during leaf development. Additional isoforms of TcCYSPR04 appeared in senescent leaves and cacao tissues infected by Moniliophthora perniciosa during the transition from the biotrophic to the saprophytic phase. TcCYSPR04 was induced in the apoplastic fluid of Catongo and TSH1188 cacao genotypes, susceptible and resistant to M. perniciosa, respectively, but greater intensity and additional isoforms were observed in TSH1188. The fungal protein MpNEP induced PLCP isoform expression in tobacco leaves, according to the cross reaction with anti-TcCYSPR04. Several protein isoforms were detected at 72 hours after treatment with MpNEP. We captured an active PLCP from cacao tissues, using a recombinant cacao cystatin immobilized in CNBr-Sepharose. Mass spectrometry showed that this protein corresponds to TcCYSPR04. A homology modeling was obtained for both proteins. In order to become active, TcCYSPR04 needs to lose its inhibitory domain. Molecular docking showed the physical-chemical complementarities of the interaction between the cacao enzyme and its inhibitor. We propose that TcCYSPR04 and its interactions with cacao cystatins are involved in the senescence and necrosis events related to witches’ broom symptoms. This molecular interaction may be the target for future interventions to control witches' broom disease. PMID:26641247

TcCYPR04, a Cacao Papain-Like Cysteine-Protease Detected in Senescent and Necrotic Tissues Interacts with a Cystatin TcCYS4.

PubMed

Cardoso, Thyago Hermylly Santana; Freitas, Ana Camila Oliveira; Andrade, Bruno Silva; Sousa, Aurizangela Oliveira de; Santiago, André da Silva; Koop, Daniela Martins; Gramacho, Karina Peres; Alvim, Fátima Cerqueira; Micheli, Fabienne; Pirovani, Carlos Priminho

2015-01-01

The interaction amongst papain-like cysteine-proteases (PLCP) and their substrates and inhibitors, such as cystatins, can be perceived as part of the molecular battlefield in plant-pathogen interaction. In cacao, four cystatins were identified and characterized by our group. We identified 448 proteases in cacao genome, whereof 134 were cysteine-proteases. We expressed in Escherichia coli a PLCP from cacao, named TcCYSPR04. Immunoblottings with anti-TcCYSPR04 exhibited protein increases during leaf development. Additional isoforms of TcCYSPR04 appeared in senescent leaves and cacao tissues infected by Moniliophthora perniciosa during the transition from the biotrophic to the saprophytic phase. TcCYSPR04 was induced in the apoplastic fluid of Catongo and TSH1188 cacao genotypes, susceptible and resistant to M. perniciosa, respectively, but greater intensity and additional isoforms were observed in TSH1188. The fungal protein MpNEP induced PLCP isoform expression in tobacco leaves, according to the cross reaction with anti-TcCYSPR04. Several protein isoforms were detected at 72 hours after treatment with MpNEP. We captured an active PLCP from cacao tissues, using a recombinant cacao cystatin immobilized in CNBr-Sepharose. Mass spectrometry showed that this protein corresponds to TcCYSPR04. A homology modeling was obtained for both proteins. In order to become active, TcCYSPR04 needs to lose its inhibitory domain. Molecular docking showed the physical-chemical complementarities of the interaction between the cacao enzyme and its inhibitor. We propose that TcCYSPR04 and its interactions with cacao cystatins are involved in the senescence and necrosis events related to witches' broom symptoms. This molecular interaction may be the target for future interventions to control witches' broom disease.

The Use of Ambient Humidity Conditions to Improve Influenza Forecast

NASA Astrophysics Data System (ADS)

Shaman, J. L.; Kandula, S.; Yang, W.; Karspeck, A. R.

2017-12-01

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast and provide further evidence that humidity modulates rates of influenza transmission.

Forecasting Japanese encephalitis incidence from historical morbidity patterns: Statistical analysis with 27 years of observation in Assam, India.

PubMed

Handique, Bijoy K; Khan, Siraj A; Mahanta, J; Sudhakar, S

2014-09-01

Japanese encephalitis (JE) is one of the dreaded mosquito-borne viral diseases mostly prevalent in south Asian countries including India. Early warning of the disease in terms of disease intensity is crucial for taking adequate and appropriate intervention measures. The present study was carried out in Dibrugarh district in the state of Assam located in the northeastern region of India to assess the accuracy of selected forecasting methods based on historical morbidity patterns of JE incidence during the past 22 years (1985-2006). Four selected forecasting methods, viz. seasonal average (SA), seasonal adjustment with last three observations (SAT), modified method adjusting long-term and cyclic trend (MSAT), and autoregressive integrated moving average (ARIMA) have been employed to assess the accuracy of each of the forecasting methods. The forecasting methods were validated for five consecutive years from 2007-2012 and accuracy of each method has been assessed. The forecasting method utilising seasonal adjustment with long-term and cyclic trend emerged as best forecasting method among the four selected forecasting methods and outperformed the even statistically more advanced ARIMA method. Peak of the disease incidence could effectively be predicted with all the methods, but there are significant variations in magnitude of forecast errors among the selected methods. As expected, variation in forecasts at primary health centre (PHC) level is wide as compared to that of district level forecasts. The study showed that adopted forecasting techniques could reasonably forecast the intensity of JE cases at PHC level without considering the external variables. The results indicate that the understanding of long-term and cyclic trend of the disease intensity will improve the accuracy of the forecasts, but there is a need for making the forecast models more robust to explain sudden variation in the disease intensity with detail analysis of parasite and host population

Forecasting forecast skill

NASA Technical Reports Server (NTRS)

Kalnay, Eugenia; Dalcher, Amnon

1987-01-01

It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Preliminary Results with Very Severe Cyclonic Storm Nargis (2008)

NASA Astrophysics Data System (ADS)

Shen, B.; Tao, W.; Atlas, R.

2008-12-01

Very Severe Cyclonic Storm Nargis, the deadliest named tropical cyclone (TC) in the North Indian Ocean Basin, devastated Burma (Myanmar) in May 2008, causing tremendous damage and numerous fatalities. An increased lead time in the prediction of TC Nargis would have increased the warning time and may therefore have saved lives and reduced economic damage. Recent advances in high-resolution global models and supercomputers have shown the potential for improving TC track and intensity forecasts, presumably by improving multi-scale simulations. The key but challenging questions to be answered include: (1) if and how realistic, in terms of timing, location and TC general structure, the global mesoscale model (GMM) can simulate TC genesis and (2) under what conditions can the model extend the lead time of TC genesis forecasts. In this study, we focus on genesis prediction for TCs in the Indian Ocean with the GMM. Preliminary real-data simulations show that the initial formation and intensity variations of TC Nargis can be realistically predicted at a lead time of up to 5 days. These simulations also suggest that the accurate representations of a westerly wind burst (WWB) and an equatorial trough, associated with monsoon circulations and/or a Madden-Julian Oscillation (MJO), are important for predicting the formation of this kind of TC. In addition to the WWB and equatorial trough, other favorable environmental conditions will be examined, which include enhanced monsoonal circulation, upper-level outflow, low- and middle-level moistening, and surface fluxes.

Using Collar worn Sensors to Forecast Thermal Strain in Military Working Dogs

DTIC Science & Technology

2016-04-22

Using Collar-worn Sensors to Forecast Thermal Strain in Military Working Dogs James R. Williamson, Austin R. Hess, Christopher J. Smalt, Delsey M...Medicine Natick, MA 01760 Abstract—Military working dogs (MWDs) are at high risk of heat strain both during training and missions. Body heat in MWD...correlation of r=0.49 between actual and predicted Tc. I. INTRODUCTION Military Working Dogs (MWDs), working in a team with a handler, are susceptible

Counteracting structural errors in ensemble forecast of influenza outbreaks.

PubMed

Pei, Sen; Shaman, Jeffrey

2017-10-13

For influenza forecasts generated using dynamical models, forecast inaccuracy is partly attributable to the nonlinear growth of error. As a consequence, quantification of the nonlinear error structure in current forecast models is needed so that this growth can be corrected and forecast skill improved. Here, we inspect the error growth of a compartmental influenza model and find that a robust error structure arises naturally from the nonlinear model dynamics. By counteracting these structural errors, diagnosed using error breeding, we develop a new forecast approach that combines dynamical error correction and statistical filtering techniques. In retrospective forecasts of historical influenza outbreaks for 95 US cities from 2003 to 2014, overall forecast accuracy for outbreak peak timing, peak intensity and attack rate, are substantially improved for predicted lead times up to 10 weeks. This error growth correction method can be generalized to improve the forecast accuracy of other infectious disease dynamical models.Inaccuracy of influenza forecasts based on dynamical models is partly due to nonlinear error growth. Here the authors address the error structure of a compartmental influenza model, and develop a new improved forecast approach combining dynamical error correction and statistical filtering techniques.

Monitoring Tc dynamics in a bioreduced sediment: an investigation with gamma camera imaging of (99m)Tc-pertechnetate and (99m)Tc-DTPA.

PubMed

Vandehey, Nicholas T; O'Neil, James P; Slowey, Aaron J; Boutchko, Rostyslav; Druhan, Jennifer L; Moses, William W; Nico, Peter S

2012-11-20

We demonstrate the utility of nuclear medical imaging technologies and a readily available radiotracer, [(99m)Tc]TcO(4)(-), for the noninvasive monitoring of Fe(II) production in acetate-stimulated sediments from Old Rifle, CO, USA. Microcosms consisting of sediment in artificial groundwater media amended with acetate were probed by repeated injection of radiotracer over three weeks. Gamma camera imaging was used to noninvasively quantify the rate and extent of [(99m)Tc]TcO(4)(-) partitioning from solution to sediment. Aqueous Fe(II) and sediment-associated Fe(II) were also measured and correlated with the observed tracer behavior. For each injection of tracer, curves of (99m)Tc concentration in solution vs time were fitted to an analytic function that accounts for both the observed rate of sedimentation as well as the rate of (99m)Tc association with the sediment. The rate and extent of (99m)Tc association with the biostimulated sediment correlated well with the production of Fe(II), and a mechanism of [(99m)Tc]TcO(4)(-) reduction via reaction with surface-bound Fe(II) to form an immobile Tc(IV) species was inferred. After three weeks of bioreduction, a subset of microcosms was aerated in order to reoxidize the Fe(II) to Fe(III), which also destroyed the affinity of the [(99m)Tc]TcO(4)(-) for the sediments. However, within 3 days postoxidation, the rate of Tc(VII) reduction was faster than immediately before oxidation implying a rapid return to more extensive bioreduction. Furthermore, aeration soon after a tracer injection showed that sediment-bound Tc(IV) is rapidly resolubilized to Tc(VII). In contrast to the [(99m)Tc]TcO(4)(-), a second commercially available tracer, (99m)Tc-DTPA (diethylenetriaminepentaacetic acid), had minimal association with sediment in both controls and biostimulated sediments. These experiments show the promise of [(99m)Tc]TcO(4)(-) and (99m)Tc-DTPA as noninvasive imaging probes for a redox-sensitive radiotracer and a conservative flow

Do location specific forecasts pose a new challenge for communicating uncertainty?

NASA Astrophysics Data System (ADS)

Abraham, Shyamali; Bartlett, Rachel; Standage, Matthew; Black, Alison; Charlton-Perez, Andrew; McCloy, Rachel

2015-04-01

In the last decade, the growth of local, site-specific weather forecasts delivered by mobile phone or website represents arguably the fastest change in forecast consumption since the beginning of Television weather forecasts 60 years ago. In this study, a street-interception survey of 274 members of the public a clear first preference for narrow weather forecasts above traditional broad weather forecasts is shown for the first time, with a clear bias towards this preference for users under 40. The impact of this change on the understanding of forecast probability and intensity information is explored. While the correct interpretation of the statement 'There is a 30% chance of rain tomorrow' is still low in the cohort, in common with previous studies, a clear impact of age and educational attainment on understanding is shown, with those under 40 and educated to degree level or above more likely to correctly interpret it. The interpretation of rainfall intensity descriptors ('Light', 'Moderate', 'Heavy') by the cohort is shown to be significantly different to official and expert assessment of the same descriptors and to have large variance amongst the cohort. However, despite these key uncertainties, members of the cohort generally seem to make appropriate decisions about rainfall forecasts. There is some evidence that the decisions made are different depending on the communication format used, and the cohort expressed a clear preference for tabular over graphical weather forecast presentation.

Use of AIRS-derived Products in Tropical Cyclone Intensity Analysis During the HS3 Field Experiment

NASA Astrophysics Data System (ADS)

Garms, E.; Knuteson, R. O.; Plokhenko, Y.; Smith, W.; Weisz, E.; Revercomb, H. E.; Ackerman, S. A.

2012-12-01

The high-resolution data collected during a field experiment is extremely valuable, but it is equally valuable to have observations that provide context for such in situ measurements. For this reason, satellite data coincident with observations taken from the Global Hawk UAVs during the Hurricane and Severe Storm Sentinel (HS3) field experiment are vital to a gaining a more complete understanding of tropical cyclone (TC) processes. The primary data used in this study are calibrated hyperspectral infrared radiances obtained from the NASA Atmospheric Infrared Sounder (AIRS), onboard the Aqua satellite. AIRS measures upwelling Earth-emitted infrared spectra using more than 2300 IR channels between 3.7 and 15.4 microns. Several products derived from this high-spectral resolution data are used in this study. These products include a 3-D cloud amount vertical profile (CAVP) product as well as temperature and water vapor profiles retrieved using a Dual-Regression algorithm (DR), both of which were developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) Cooperative Institute for Meteorological Satellite Studies (CIMSS). The CAVP product will be used to measure the slope of the cloud tops of rainbands in a tropical cyclone. Observations from the UW Scanning High-resolution Interferometer Sounder (S-HIS), NASA Micro Pulse Lidar (MPL), and NCAR dropsondes taken during the 2012 Hurricane and Severe Storm Sentinel (HS3) field experiment will be used to validate the rainband slope analysis and the DR retrievals. The methodology behind the TC rainband slope analysis, which is hypothesized to correlate with TC intensity, will be discussed. This product will then be used to obtain a TC intensity estimate, which will be compared to other accepted intensity estimates like the Advanced Dvorak Technique (ADT), Advanced Microwave Sounding Unit (AMSU), and Satellite Consensus (SATCON) estimates. Additionally, the DR product will be used to

Altered [99mTc]Tc-MDP biodistribution from neutron activation sourced 99Mo.

PubMed

Demeter, Sandor; Szweda, Roman; Patterson, Judy; Grigoryan, Marine

2018-01-01

Given potential worldwide shortages of fission sourced 99 Mo/ 99m Tc medical isotopes there is increasing interest in alternate production strategies. A neutron activated 99 Mo source was utilized in a single center phase III open label study comparing 99m Tc, as 99m Tc Methylene Diphosphonate ([ 99m Tc]Tc-MDP), obtained from solvent generator separation of neutron activation produced 99 Mo, versus nuclear reactor produced 99 Mo (e.g., fission sourced) in oncology patients for which an [ 99m Tc]Tc-MDP bone scan would normally have been indicated. Despite the investigational [ 99m Tc]Tc-MDP passing all standard, and above standard of care, quality assurance tests, which would normally be sufficient to allow human administration, there was altered biodistribution which could lead to erroneous clinical interpretation. The cause of the altered biodistribution remains unknown and requires further research.

Prediction of Intensity Change Subsequent to Concentric Eyewall Events

NASA Astrophysics Data System (ADS)

Mauk, Rachel Grant

Concentric eyewall events have been documented numerous times in intense tropical cyclones over the last two decades. During a concentric eyewall event, an outer (secondary) eyewall forms around the inner (primary) eyewall. Improved instrumentation on aircraft and satellites greatly increases the likelihood of detecting an event. Despite the increased ability to detect such events, forecasts of intensity changes during and after these events remain poor. When concentric eyewall events occur near land, accurate intensity change predictions are especially critical to ensure proper emergency preparations and staging of recovery assets. A nineteen-year (1997-2015) database of concentric eyewall events is developed by analyzing microwave satellite imagery, aircraft- and land-based radar, and other published documents. Events are identified in both the North Atlantic and eastern North Pacific basins. TCs are categorized as single (1 event), serial (>= 2 events) and super-serial (>= 3 events). Key findings here include distinct spatial patterns for single and serial Atlantic TCs, a broad seasonal distribution for eastern North Pacific TCs, and apparent ENSO-related variability in both basins. The intensity change subsequent to the concentric eyewall event is calculated from the HURDAT2 database at time points relative to the start and to the end of the event. Intensity change is then categorized as Weaken (≤ -10 kt), Maintain (+/- 5 kt), and Strengthen (≥ 10 kt). Environmental conditions in which each event occurred are analyzed based on the SHIPS diagnostic files. Oceanic, dynamic, thermodynamic, and TC status predictors are selected for testing in a multiple discriminant analysis procedure to determine which variables successfully discriminate the intensity change category and the occurrence of additional concentric eyewall events. Intensity models are created for 12 h, 24 h, 36 h, and 48 h after the concentric eyewall events end. Leave-one-out cross validation is

State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems.

PubMed

Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R; Madsen, Henrik

2013-01-01

Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control.

NOAA's weather forecasts go hyper-local with next-generation weather

Science.gov Websites

model NOAA HOME WEATHER OCEANS FISHERIES CHARTING SATELLITES CLIMATE RESEARCH COASTS CAREERS with next-generation weather model New model will help forecasters predict a storm's path, timing and intensity better than ever September 30, 2014 This is a comparison of two weather forecast models looking

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.

Performance of TcI/TcVI/TcII Chagas-Flow ATE-IgG2a for universal and genotype-specific serodiagnosis of Trypanosoma cruzi infection

PubMed Central

Alessio, Glaucia Diniz; de Araújo, Fernanda Fortes; Côrtes, Denise Fonseca; Sales Júnior, Policarpo Ademar; Lima, Daniela Cristina; Gomes, Matheus de Souza; do Amaral, Laurence Rodrigues; Xavier, Marcelo Antônio Pascoal; Teixeira-Carvalho, Andréa; Martins-Filho, Olindo Assis; de Lana, Marta

2017-01-01

Distinct Trypanosoma cruzi genotypes have been considered relevant for patient management and therapeutic response of Chagas disease. However, typing strategies for genotype-specific serodiagnosis of Chagas disease are still unavailable and requires standardization for practical application. In this study, an innovative TcI/TcVI/TcII Chagas Flow ATE-IgG2a technique was developed with applicability for universal and genotype-specific diagnosis of T. cruzi infection. For this purpose, the reactivity of serum samples (percentage of positive fluorescent parasites-PPFP) obtained from mice chronically infected with TcI/Colombiana, TcVI/CL or TcII/Y strain as well as non-infected controls were determined using amastigote-AMA, trypomastigote-TRYPO and epimastigote-EPI in parallel batches of TcI, TcVI and TcII target antigens. Data demonstrated that “α-TcII-TRYPO/1:500, cut-off/PPFP = 20%” presented an excellent performance for universal diagnosis of T. cruzi infection (AUC = 1.0, Se and Sp = 100%). The combined set of attributes “α-TcI-TRYPO/1:4,000, cut-off/PPFP = 50%”, “α-TcII-AMA/1:1,000, cut-off/PPFP = 40%” and “α-TcVI-EPI/1:1,000, cut-off/PPFP = 45%” showed good performance to segregate infections with TcI/Colombiana, TcVI/CL or TcII/Y strain. Overall, hosts infected with TcI/Colombiana and TcII/Y strains displayed opposite patterns of reactivity with “α-TcI TRYPO” and “α-TcII AMA”. Hosts infected with TcVI/CL strain showed a typical interweaved distribution pattern. The method presented a good performance for genotype-specific diagnosis, with global accuracy of 69% when the population/prototype scenario include TcI, TcVI and TcII infections and 94% when comprise only TcI and TcII infections. This study also proposes a receiver operating reactivity panel, providing a feasible tool to classify serum samples from hosts infected with distinct T. cruzi genotypes, supporting the potential of this method for universal and genotype

Communicating Storm Surge Forecast Uncertainty

NASA Astrophysics Data System (ADS)

Troutman, J. A.; Rhome, J.

2015-12-01

When it comes to tropical cyclones, storm surge is often the greatest threat to life and property along the coastal United States. The coastal population density has dramatically increased over the past 20 years, putting more people at risk. Informing emergency managers, decision-makers and the public about the potential for wind driven storm surge, however, has been extremely difficult. Recently, the Storm Surge Unit at the National Hurricane Center in Miami, Florida has developed a prototype experimental storm surge watch/warning graphic to help communicate this threat more effectively by identifying areas most at risk for life-threatening storm surge. This prototype is the initial step in the transition toward a NWS storm surge watch/warning system and highlights the inundation levels that have a 10% chance of being exceeded. The guidance for this product is the Probabilistic Hurricane Storm Surge (P-Surge) model, which predicts the probability of various storm surge heights by statistically evaluating numerous SLOSH model simulations. Questions remain, however, if exceedance values in addition to the 10% may be of equal importance to forecasters. P-Surge data from 2014 Hurricane Arthur is used to ascertain the practicality of incorporating other exceedance data into storm surge forecasts. Extracting forecast uncertainty information through analyzing P-surge exceedances overlaid with track and wind intensity forecasts proves to be beneficial for forecasters and decision support.

Bone marrow uptake of 99mTc-MIBI in patients with multiple myeloma.

PubMed

Fonti, R; Del Vecchio, S; Zannetti, A; De Renzo, A; Di Gennaro, F; Catalano, L; Califano, C; Pace, L; Rotoli, B; Salvatore, M

2001-02-01

In a previous study, we showed the ability of technetium-99m methoxyisobutylisonitrile (99mTc-MIBI) scan to identify active disease in patients with multiple myeloma (Eur J Nucl Med 1998; 25: 714-720). In particular, a semiquantitative score of the extension and intensity of bone marrow uptake was derived and correlated with both the clinical status of the disease and plasma cell bone marrow infiltration. In order to estimate quantitatively 99mTc-MIBI bone marrow uptake and to verify the intracellular localization of the tracer, bone marrow samples obtained from 24 multiple myeloma patients, three patients with monoclonal gammopathy of undetermined significance (MGUS) and two healthy donors were studied for in vitro uptake. After centrifugation over Ficoll-Hypaque gradient, cell suspensions were incubated with 99mTc-MIBI and the uptake was expressed as the percentage of radioactivity specifically retained within the cells. The cellular localization of the tracer was assessed by micro-autoradiography. Twenty-two out of 27 patients underwent 99mTc-MIBI scan within a week of bone marrow sampling. Whole-body images were obtained 10 min after intravenous injection of 555 MBq of the tracer; the extension and intensity of 99mTc-MIBI uptake were graded using the semiquantitative score. A statistically significant correlation was found between in vitro uptake of 99mTc-MIBI and both plasma cell infiltration (Pearson's coefficient of correlation r=0.69, P<0.0001) and in vivo score (Spearman rank correlation coefficient r=0.60, P<0.01). No specific tracer uptake was found in bone marrow samples obtained from the two healthy donors. Micro-autoradiography showed localization of 99mTc-MIBI inside the plasma cells infiltrating the bone marrow. Therefore, our findings show that the degree of tracer uptake both in vitro and in vivo is related to the percentage of infiltrating plasma cells which accumulate the tracer in their inner compartments.

Training Guide for Severe Weather Forecasters

DTIC Science & Technology

1979-11-01

that worked very well for the example forecast is used to show the importance of parameter intensities and the actual thought processes that go into the...simplify the explanation of the complete level analysis. This entire process will be repeated for the 700 mb and 500 mb levels. Details in Figures 1 through...parameters of moderate to strong intensity must occur, in the same place at the same time. A description of what constitutes a weak, moderate, or strong

99 Tc NMR determination of the oxygen isotope content in 18 O-enriched water.

PubMed

Tarasov, Valerii P; Kirakosyan, Gayana А; German, Konstantin E

2018-03-01

99 Tc NMR has been suggested as an original method of evaluating the content of oxygen isotopes in oxygen-18-enriched water, a precursor for the production of radioisotope fluorine-18 used in positron emission tomography. To this end, solutions of NH 4 TcO 4 or NaTcO 4 (up to 0.28 mol/L) with natural abundance of oxygen isotopes in virgin or recycled 18 O-enriched water have been studied by 99 Tc NMR. The method is based on 16 O/ 17 O/ 18 O intrinsic isotope effects in the 99 Tc NMR chemical shifts, and the statistical distribution of oxygen isotopes in the coordination sphere of TcO 4 - and makes it possible to quantify the composition of enriched water by measuring the relative intensities of the 99 Tc NMR signals of the Tc 16 O 4-n 18 O n - isotopologues. Because the oxygen exchange between TcO 4 - and enriched water in neutral and alkaline solutions is characterized by slow kinetics, gaseous HCl was bubbled through a solution for a few seconds to achieve the equilibrium distribution of oxygen isotopes in the Tc coordination sphere without distortion of the oxygen composition of the water. Pertechnetate ion was selected as a probe due to its high stability in solutions and the significant 99 Tc NMR shift induced by a single 16 O→ 18 O substitution (-0.43 ± 0.01 ppm) in TcO 4 - and spin coupling constant 1 J( 99 Tc- 17 O) (131.46 Hz) favourable for the observation of individual signals of Tc 16 O 4-n 18 O n - isotopologues. Copyright © 2017 John Wiley & Sons, Ltd.

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

NASA Astrophysics Data System (ADS)

Choi, Yonghan; Cha, Dong-Hyun; Lee, Myong-In; Kim, Joowan; Jin, Chun-Sil; Park, Sang-Hun; Joh, Min-Su

2017-06-01

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.

Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

NASA Technical Reports Server (NTRS)

Hlavka, Dennis; Tian, Lin; Hart, William; Li, Lihua; McGill, Matthew; Heymsfield, Gerald

2009-01-01

Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy

Calls Forecast for the Moscow Ambulance Service. The Impact of Weather Forecast

NASA Astrophysics Data System (ADS)

Gordin, Vladimir; Bykov, Philipp

2015-04-01

result we hope to evaluate how weather can influence the intensity of the disease. Thus, the knowledge of the weather forecast for several days will help us to predict a state of health. The person will be able to take some proactive actions to avoid the anticipated worsening of his health. Literature 1. A. N. Bagrov, F. L. Bykov, V. A. Gordin. Complex Forecast of Surface Meteorological Parameters. Meteorology and Hydrology, 2014, N 5, 5-16 (Russian), 283-291 (English). 2. Bykov, Ph.L., Gordin, V.A., Objective Analysis of the Structure of Three-Dimensional Atmospheric Fronts. Izvestia of Russian Academy of Sciences. Ser. The Physics of Atmosphere and Ocean, 48 (2) (2012), 172-188 (Russian), 152-168 (English), http://dx.doi.org/10.1134/S0001433812020053 3. V.A.Gordin. Mathematical Problems and Methods in Hydrodynamical Weather Forecasting. Amsterdam etc.: Gordon & Breach Publ. House, 2000. 4. V.A.Gordin. Mathematics, Computer, Weather Forecasting, and Other Mathematical Physics' Scenarios. Moscow, Fizmatlit, 2010, 2012 (Russian).

Development of Tc(IV)-Incorporated Fe Minerals to Enhance 99Tc Retention in Glass Waste Form

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

Um, Wooyong; Luksic, Steven A.; Wang, Guohui

Iron minerals have been considered to be good hosts for Tc immobilization because the Tc(IV) ion substitutes for Fe(III) in the crystal structure of the Fe oxide due to similarities in (1) cation size [Tc(IV) = 78.5 pm ; Fe(III) = 69 or 78.5 pm], (2) metal-oxygen interatomic distance (Tc—O = 0.199 nm, Fe—O = 0.203 nm), (3) number of coordinating oxygen atoms (both 6-fold coordinated), and (4) the redox potential (Eh=ca. +20 mV at pH = 7) for a redox couple between Tc(VII)/Tc(IV) and Fe(III)/Fe(II). Magnetite, maghemite, and trevorite are iron oxide minerals and all belong to spinel mineralmore » group. Laboratory testing shows that Tc can be removed from aqueous waste solutions by a process of Tc reduction from Tc(VII) to Tc(IV) followed by co-precipitation with iron oxide minerals during recrystallization of Fe(OH)2(s) used as an initial solid precursor. X-ray absorption near edge structure (XANES) spectroscopy confirmed that Tc was in the +4 oxidation state in final Tc-Fe minerals. The Tc-incorporated Fe minerals were also tested for Tc retention in glass melts at different temperatures between 600 – 1,000 oC in a furnace. After being cooled in air, the solid glass specimens collected at different temperatures were analyzed for Tc oxidation state using XANES and Tc retention using liquid scintillation counting (LSC). Even though Tc(IV) started to reoxidize at 600 oC, Tc retention in the final glass specimen prepared with Tc-incorporated Fe mineral even at high temperatures was at least two times higher than glass prepared with KTcO4 salt. Higher Tc retention in glass is considered to result from limited and delayed Tc volatilization process due to Fe mineral encapsulation for Tc. Therefore, the results showing the presence of Tc(IV) in the Fe mineral structure indicate strong possibility to enhance Tc retention in borosilicate glass as well as to reduce the remediation costs at the Hanford Site.« less

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.

Mean Bias in Seasonal Forecast Model and ENSO Prediction Error.

PubMed

Kim, Seon Tae; Jeong, Hye-In; Jin, Fei-Fei

2017-07-20

This study uses retrospective forecasts made using an APEC Climate Center seasonal forecast model to investigate the cause of errors in predicting the amplitude of El Niño Southern Oscillation (ENSO)-driven sea surface temperature variability. When utilizing Bjerknes coupled stability (BJ) index analysis, enhanced errors in ENSO amplitude with forecast lead times are found to be well represented by those in the growth rate estimated by the BJ index. ENSO amplitude forecast errors are most strongly associated with the errors in both the thermocline slope response and surface wind response to forcing over the tropical Pacific, leading to errors in thermocline feedback. This study concludes that upper ocean temperature bias in the equatorial Pacific, which becomes more intense with increasing lead times, is a possible cause of forecast errors in the thermocline feedback and thus in ENSO amplitude.

Results from the second year of a collaborative effort to forecast influenza seasons in the United States.

PubMed

Biggerstaff, Matthew; Johansson, Michael; Alper, David; Brooks, Logan C; Chakraborty, Prithwish; Farrow, David C; Hyun, Sangwon; Kandula, Sasikiran; McGowan, Craig; Ramakrishnan, Naren; Rosenfeld, Roni; Shaman, Jeffrey; Tibshirani, Rob; Tibshirani, Ryan J; Vespignani, Alessandro; Yang, Wan; Zhang, Qian; Reed, Carrie

2018-02-24

Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for the United States and the 10 Health and Human Service Regions. Forecasted targets for the 2014-15 challenge were the onset week, peak week, and peak intensity of the season and the weekly percent of outpatient visits due to influenza-like illness (ILI) 1-4 weeks in advance. We used a logarithmic scoring rule to score the weekly forecasts, averaged the scores over an evaluation period, and then exponentiated the resulting logarithmic score. Poor forecasts had a score near 0, and perfect forecasts a score of 1. Five teams submitted forecasts from seven different models. At the national level, the team scores for onset week ranged from <0.01 to 0.41, peak week ranged from 0.08 to 0.49, and peak intensity ranged from <0.01 to 0.17. The scores for predictions of ILI 1-4 weeks in advance ranged from 0.02-0.38 and was highest 1 week ahead. Forecast skill varied by HHS region. Forecasts can predict epidemic characteristics that inform public health actions. CDC, state and local health officials, and researchers are working together to improve forecasts. Published by Elsevier B.V.

Model Projections and their Uncertainties of Future Intensity Change of Typhoon Haiyan (2013)

NASA Astrophysics Data System (ADS)

Yoshino, J.; Toyoda, M.; Shinohara, K.; Kobayashi, T.

2017-12-01

The IPCC fifth assessment report indicated that the global mean maximum wind speed and precipitation of tropical cyclone (TC) are likely to increase by the end of 21st century. However, the specific characteristics of future changes are not yet well quantified and there are high uncertainties in region-specific projections. Such uncertainties in future projections may be attributed to the uncertainties of general circulation models (GCMs) and global warming scenarios (GWSs). In order to quantify uncertainties of future changes of TC intensity among 15 GCMs and 9 GWSs, a present climate experiment (PCE), future climate experiments (FCEs) and sensitivity experiments on TC intensity are carried out in this study using a high-resolution typhoon model, coupled with sea spray, dissipative heating, ocean mixed layer parameterizations and automatic-TC tracking moving nests. The initial and boundary conditions for FCEs are produced by the method of pseudo-global warming downscaling technique. Typhoon Haiyan (2013) is selected as the worst case of a TC under the present climate. Using the high-resolution typhoon model with a grid spacing of 3km, PCE reproduces a peak intensity (minimum central pressure) of about 897.1hPa, which is in close agreement with the besttrack data (895hPa). Comparing the results between 9 FCEs driven by 9 GCMs fixed by one of GCMs (HadCM3) and 15 FCEs driven by 15 GWSs fixed by one of GWSs (in the 2090s of SRES A1B), the TC intensities are slightly weakened by +7.9hPa for GCMs and +3.7hPa for GWSs. The standard deviations of future changes of the peak intensity are 9.47hPa for GCMs and 5.89hPa for GWSs. Thus, the uncertainty of future changes of TC intensity among GCMs is approximately two times larger than that among GWSs. Sensitivity experiments, in which each of global warming differences derived from GCMs are separately added to the initial and boundary conditions of PCE, suggest that the future changes of sea surface temperature in GCMs are

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

Anomalous Normal State and Quasi Particle Transport in High-Tc Superconductors

NASA Astrophysics Data System (ADS)

Ong, N. P.

1997-03-01

The quasi-particles (qp) below Tc are much less studied compared to excitations of the normal state. The thermal conductivity tensor κ_ij provides a window on their transport properties. In YBaCuO, the large thermal Hall response allows the qp mean-free-path l to be estimated. l rises rapidly from 90 Åat Tc to over 6,000 Åat 20 K in untwinned crystals. The intense scattering rate above Tc is rapidly suppressed, leaving qp's that travel great distances at low T. In LaSrCuO, where there is substantial disorder, κ_xx varies logarithmically with field B. While the field dependence is entirely electronic, it is incompatible with scattering from vortices. κ_xx fits well to the digamma function form ψ(1/2+ fracB_0B) + ln(fracBB_0), with a T-linear field-scale B_0. Possible field destruction of a quantum interference effect or depairing effects in a d-wave superconductor will be discussed.

The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature

DOE PAGES

Strazzo, S. E.; Elsner, J. B.; LaRow, T. E.; ...

2016-07-10

Global climate models (GCMs) are routinely relied upon to study the possible impacts of climate change on a wide range of meteorological phenomena, including tropical cyclones (TCs). Previous studies addressed whether GCMs are capable of reproducing observed TC frequency and intensity distributions. This research builds upon earlier studies by examining how well GCMs capture the physically relevant relationship between TC intensity and SST. Specifically, the influence of model resolution on the ability of a GCM to reproduce the sensitivity of simulated TC intensity to SST is examined for the MRI-AGCM (20 km), the GFDL-HiRAM (50 km), the FSU-COAPS (0.94°) model,more » and two versions of the CAM5 (1° and 0.25°). Results indicate that while a 1°C increase in SST corresponds to a 5.5–7.0 m s -1 increase in observed maximum intensity, the same 1°C increase in SST is not associated with a statistically significant increase in simulated TC maximum intensity for any of the models examined. However, it also is shown that the GCMs all capably reproduce the observed sensitivity of potential intensity to SST. The models generate the thermodynamic environment suitable for the development of strong TCs over the correct portions of the Nort h Atlantic basin, but strong simulated TCs do not develop over these areas, even for models that permit Category 5 TCs. This result supports the notion that direct simulation of TC eyewall convection is necessary to accurately represent TC intensity and intensification processes in climate models, although additional explanations are also explored.« less

PREFACE: 2014 Joint IMEKO TC1-TC7-TC13 Symposium: Measurement Science Behind Safety and Security

NASA Astrophysics Data System (ADS)

Sousa, João A.; Ribeiro, Álvaro S.; Filipe, Eduarda

2015-02-01

The 2014 Joint IMEKO (International Measurement Confederation) TC1-TC7-TC13 Symposium was organized by RELACRE - Portuguese Association of Accredited Laboratories and the Portuguese Society for Metrology, on 3-5 September 2014. The work of this symposium is reported in this volume. The scope of the symposium includes the main topics covered by the above Technical Committees: - TC1 Education and Training in measurement and Instrumentation - TC7 Measurement Science - TC13 Measurements in Biology and Medicine The effort towards excellence of previous events, in this well established series, is maintained. There has been a special focus on measurement science behind safety and security, with the aim of highlighting the interdisciplinary character of measurement science and the importance of metrology in our daily lives. The discussion was introduced by keynote lectures on measurement challenges in biometrics, health monitoring and social sciences, to promote useful interactions with scientists from different disciplines. The Symposium was attended by experts working in these areas from 18 countries, including USA, Japan and China, and provided a useful forum for them to share and exchange their work and ideas. In total over fifty papers are included in the volume, organized according to the presentation sessions. Each paper was independently peer-reviewed by two reviewers from a distinguished international panel. The Symposium was held in Funchal, capital of Madeira Islands, known as the Atlantic Pearl. This wonderful Atlantic archipelago, formed by Madeira and Porto Santo islands, discovered in the 14th century, was chosen to host the 2014 IMEKO TC1-TC7-TC13 Joint Symposium ''Measurement Science behind Safety and Security''. It was the first territory discovered by the Portuguese sailors, when set out to discover a new world, in an epic journey where instrumentation and quality of measurement played a central role in the success of the enterprise, and gave an

Tc-99m pyrophosphate myocardial scanning in Chagas' disease

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

da Rocha, A.F.; Meguerian, B.A.; Harbert, J.C.

1981-04-01

Chagas' disease is a serious protozoan infection affecting up to 20% of populations in some endemic areas. Myocarditis and cardiomyopathy occur in 50% of patients who go on to develop chronic Chagas' disease. We have studied a patient with no overt cardiac symptoms who revealed intense myocardial uptake of Tc-99m pyrophosphate. The significance of this finding in relation to early detection and progress of therapy is explored.

Tc-99m pyrophosphate myocardial scanning in Chagas' disease

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

Goncalves da Rocha, A.F.; Meguerian, B.A.; Harbert, J.C.

1981-04-01

Chagas' disease is a serious protozoan infection affecting up to 20% of populations in some endemic areas. Myocarditis and cardiomyopathy occur in 50% of patients who go on to develop chronic Chagas's disease. We have studied a patient with no overt cardiac symptoms who revealed intense myocardial uptake of Tc-99m pyrophosphate. The significance of this finding in relation to early detection and progress of therapy is explored.

Use of Tc-99m-galactosyl-neoglycoalbumin (Tc-NGA) to determine hepatic blood flow

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

Stadalnik, R.C.; Vera, D.R.; Woodle, E.S.

1984-01-01

Tc-NGA is a new liver radiopharmaceutical which binds to a hepatocyte-specific membrane receptor. Three characteristics of Tc-NGA can be exploited in the measurement of hepatic blood flow (HBF): 1) ability to alter the affinity of Tc-NGA for its receptor by changing the galactose: albumin ratio; 2) ability to achieve a high specific activity with Tc-99m labeling; and 3) ability to administer a high molar dose of Tc-NGA without physiologic side effects. In addition, kinetic modeling of Tc-NGA dynamic data can provide estimates of hepatic receptor concentration. In experimental studies in young pigs, HBF was determined using two techniques: 1) kineticmore » modeling of dynamic data using moderate affinity, low specific activity Tc-NGA (Group A, n=12); and 2) clearance (CL) technique using high affinity, high specific activity Tc-NGA (Group B, n=4). In both groups, HBF was determined simultaneously by continuous infusion of indocyanine green (CI-ICG) with hepatic vein sampling. Regression analysis of HBF measurements obtained with the Tc-NGA kinetic modeling technique and the CI-ICG technique (Group A) revealed good correlation between the two techniques (r=0.802, p=0.02). Similarly, HBF determination by the clearance technique (Group B) provided highly accurate measurements when compared to the CI-ICG technique. Hepatic blood flow measurements by the clearance technique (CL-NGA) fell within one standard deviation of the error associated with each CI-ICG HBF measurement (all CI-ICG standard deviations were less than 10%).« less

Improved Use of Satellite Imagery to Forecast Hurricanes

NASA Technical Reports Server (NTRS)

Louis, Jean-Francois

2001-01-01

This project tested a novel method that uses satellite imagery to correct phase errors in the initial state for numerical weather prediction, applied to hurricane forecasts. The system was tested on hurricanes Guillermo (1997), Felicia (1997) and Iniki (1992). We compared the performance of the system with and without phase correction to a procedure that uses bogus data in the initial state, similar to current operational procedures. The phase correction keeps the hurricane on track in the analysis and is far superior to a system without phase correction. Compared to operational procedure, phase correction generates somewhat worse 3-day forecast of the hurricane track, but better forecast of intensity. It is believed that the phase correction module would work best in the context of 4-dimensional variational data assimilation. Very little modification to 4DVar would be required.

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

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

Lackmann, Gary

2013-06-10

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured withmore » sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance

The Impact of Assimilation of GPM Clear Sky Radiance on HWRF Hurricane Track and Intensity Forecasts

NASA Astrophysics Data System (ADS)

Yu, C. L.; Pu, Z.

2016-12-01

The impact of GPM microwave imager (GMI) clear sky radiances on hurricane forecasting is examined by ingesting GMI level 1C recalibrated brightness temperature into the NCEP Gridpoint Statistical Interpolation (GSI)- based ensemble-variational hybrid data assimilation system for the operational Hurricane Weather Research and Forecast (HWRF) system. The GMI clear sky radiances are compared with the Community Radiative Transfer Model (CRTM) simulated radiances to closely study the quality of the radiance observations. The quality check result indicates the presence of bias in various channels. A static bias correction scheme, in which the appropriate bias correction coefficients for GMI data is evaluated by applying regression method on a sufficiently large sample of data representative to the observational bias in the regions of concern, is used to correct the observational bias in GMI clear sky radiances. Forecast results with and without assimilation of GMI radiance are compared using hurricane cases from recent hurricane seasons (e.g., Hurricane Joaquin in 2015). Diagnoses of data assimilation results show that the bias correction coefficients obtained from the regression method can correct the inherent biases in GMI radiance data, significantly reducing observational residuals. The removal of biases also allows more data to pass GSI quality control and hence to be assimilated into the model. Forecast results for hurricane Joaquin demonstrates that the quality of analysis from the data assimilation is sensitive to the bias correction, with positive impacts on the hurricane track forecast when systematic biases are removed from the radiance data. Details will be presented at the symposium.

Sensitivity of the simulation of tropical cyclone size to microphysics schemes

NASA Astrophysics Data System (ADS)

Chan, Kelvin T. F.; Chan, Johnny C. L.

2016-09-01

The sensitivity of the simulation of tropical cyclone (TC) size to microphysics schemes is studied using the Advanced Hurricane Weather Research and Forecasting Model (WRF). Six TCs during the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-Ferrier (FER), WRF Single-Moment 5-class (WSM5) and WRF Single-Moment 6-class (WSM6)-are investigated. The results consistently show that the simulated TC track is not sensitive to the choice of microphysics scheme in the early simulation, especially in the open ocean. However, the sensitivity is much greater for TC intensity and inner-core size. The TC intensity and size simulated using the WSM5 and WSM6 schemes are respectively higher and larger than those using the FER scheme in general, which likely results from more diabatic heating being generated outside the eyewall in rainbands. More diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere, with higher upward motion outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall, leading to the increment in TC intensity and size (the inner-core size, especially). In addition, the inclusion of graupel microphysics processes (as in WSM6) may not have a significant impact on the simulation of TC track, intensity and size.

Earthquake forecasts for the CSEP Japan experiment based on the RI algorithm

NASA Astrophysics Data System (ADS)

Nanjo, K. Z.

2011-03-01

An earthquake forecast testing experiment for Japan, the first of its kind, is underway within the framework of the Collaboratory for the Study of Earthquake Predictability (CSEP) under a controlled environment. Here we give an overview of the earthquake forecast models, based on the RI algorithm, which we have submitted to the CSEP Japan experiment. Models have been submitted to a total of 9 categories, corresponding to 3 testing classes (3 years, 1 year, and 3 months) and 3 testing regions. The RI algorithm is originally a binary forecast system based on the working assumption that large earthquakes are more likely to occur in the future at locations of higher seismicity in the past. It is based on simple counts of the number of past earthquakes, which is called the Relative Intensity (RI) of seismicity. To improve its forecast performance, we first expand the RI algorithm by introducing spatial smoothing. We then convert the RI representation from a binary system to a CSEP-testable model that produces forecasts for the number of earthquakes of predefined magnitudes. We use information on past seismicity to tune the parameters. The final submittal consists of 36 executable computer codes: 4 variants corresponding to different smoothing parameters for each of the 9 categories. They will help to elucidate which categories and which smoothing parameters are the most meaningful for the RI hypothesis. The main purpose of our participation in the experiment is to better understand the significance of the relative intensity of seismicity for earthquake forecastability in Japan.

Identification of novel mammalian hosts and Brazilian biome geographic distribution of Trypanosoma cruzi TcIII and TcIV.

PubMed

Barros, Juliana Helena S; Xavier, Samanta Cristina C; Bilac, Daniele; Lima, Valdirene Santos; Dario, Maria Augusta; Jansen, Ana Maria

2017-08-01

Trypanosoma cruzi is a parasitic protozoan responsible for Chagas disease. Seven different Discrete Typing Units (DTUs) of T. cruzi are currently identified in nature: TcI-TcVI, and TcBat whose distribution patterns in nature, hosts/reservoirs and eco-epidemiological importance are still little known. Here, we present novel data on the geographic distribution and diversity of mammalian hosts and vectors of T. cruzi DTUs TcIII and TcIV. In this study, we analyzed 61 T. cruzi isolates obtained from 18 species of mammals (five orders) and two Hemiptera genera. Samples were collected from five Brazilian biomes (Pantanal, Caatinga, Cerrado, Atlantic Rainforest, and Amazon) previously characterized as Z3 or mixed infection (TcI-Z3) by mini-exon gene PCR. To identify TcIII and TcIV genotypes, we applied restriction fragment length polymorphism analysis to the PCR-amplified histone 3 gene. DTUs TcIII and TcIV were identified in single and mixed infections from wide dispersion throughout five Brazilian biomes studied, with TcIV being the most common. Pantanal was the biome that displayed the largest number of samples characterized as TcIII and TcIV in single and mixed infections, followed by Atlantic Rainforest and Amazon. Species from the Didelphimorphia order displayed the highest frequency of infection and were found in all five biomes. We report, for the first time, the infection of a species of the Artiodactyla order by DTU TcIII. In addition, we describe new host species: five mammals (marsupials and rodents) and two genera of Hemiptera. Our data indicate that DTUs TcIII and TcIV are more widespread and infect a larger number of mammalian species than previously thought. In addition, they are transmitted in restricted foci and cycles, but in different microhabitats and areas with distinct ecological profiles. Finally, we show that DTUs TcIII and TcIV do not present any specific association with biomes or host species. Copyright © 2017. Published by Elsevier B.V.

The role of β-effect and a uniform current on tropical cyclone intensity

NASA Astrophysics Data System (ADS)

Duan, Yihong; Wu, Rongsheng; Yu, Hui; Liang, Xudong; Chan, Johnny C. L.

2004-02-01

A limited-area primitive equation model is used to study the role of the β-effect and a uniform current on tropical cyclone (TC) intensity. It is found that TC intensity is reduced in a non-quiescent environment compared with the case of no uniform current. On an f-plane, the rate of intensification of a tropical cyclone is larger than that of the uniform flow. A TC on a β-plane intensifies slower than one on an f-plane. The main physical characteristic that distinguishes the experiments is the asymmetric thermodynamic (including convective) and dynamic structures present when either a uniform flow or β-effect is introduced. But a fairly symmetric TC structure is simulated on an f-plane. The magnitude of the warm core and the associated subsidence are found to be responsible for such simulated intensity changes. On an f-plane, the convection tends to be symmetric, which results in strong upper-level convergence near the center and hence strong forced subsidence and a very warm core. On the other hand, horizontal advection of temperature cancels part of the adiabatic heating and results in less warming of the core, and hence the TC is not as intense. This advective process is due to the tilt of the vortex as a result of the β-effect. A similar situation occurs in the presence of a uniform flow. Thus, the asymmetric horizontal advection of temperature plays an important role in the temperature distribution. Dynamically, the asymmetric angular momentum (AM) flux is very small on an f-plane throughout the troposphere. However, the total AM exports at the upper levels for a TC either on a β-plane or with a uniform flow environment are larger because of an increase of the asymmetric as well as symmetric AM export on the plane at radii >450 km, and hence there is a lesser intensification.

Affective forecasting bias in preschool children.

PubMed

Gautam, Shalini; Bulley, Adam; von Hippel, William; Suddendorf, Thomas

2017-07-01

Adults are capable of predicting their emotional reactions to possible future events. Nevertheless, they systematically overestimate the intensity of their future emotional reactions relative to how they feel when these events actually occur. The developmental origin of this "intensity bias" has not yet been examined. Two studies were conducted to test the intensity bias in preschool children. In the first study, 5-year-olds (N=30) predicted how they would feel if they won or lost various games. Comparisons with subsequent self-reported feelings indicated that participants overestimated how sad they would feel to lose the games but did not overestimate their happiness from winning. The second study replicated this effect in another sample of 5-year-olds (n=34) and also found evidence of an intensity bias in 4-year-olds (n=30). These findings provide the first evidence of a negative intensity bias in affective forecasting among young children. Copyright © 2017 Elsevier Inc. All rights reserved.

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

In-house cyclotron production of high-purity Tc-99m and Tc-99m radiopharmaceuticals.

PubMed

Martini, Petra; Boschi, Alessandra; Cicoria, Gianfranco; Zagni, Federico; Corazza, Andrea; Uccelli, Licia; Pasquali, Micòl; Pupillo, Gaia; Marengo, Mario; Loriggiola, Massimo; Skliarova, Hanna; Mou, Liliana; Cisternino, Sara; Carturan, Sara; Melendez-Alafort, Laura; Uzunov, Nikolay M; Bello, Michele; Alvarez, Carlos Rossi; Esposito, Juan; Duatti, Adriano

2018-05-30

In the last years, the technology for producing the important medical radionuclide technetium-99m by cyclotrons has become sufficiently mature to justify its introduction as an alternative source of the starting precursor [ 99m Tc][TcO 4 ] - ubiquitously employed for the production of 99m Tc-radiopharmaceuticals in hospitals. These technologies make use almost exclusively of the nuclear reaction 100 Mo(p,2n) 99m Tc that allows direct production of Tc-99m. In this study, it is conjectured that this alternative production route will not replace the current supply chain based on the distribution of 99 Mo/ 99m Tc generators, but could become a convenient emergency source of Tc-99m only for in-house hospitals equipped with a conventional, low-energy, medical cyclotron. On this ground, an outline of the essential steps that should be implemented for setting up a hospital radiopharmacy aimed at the occasional production of Tc-99m by a small cyclotron is discussed. These include (1) target production, (2) irradiation conditions, (3) separation/purification procedures, (4) terminal sterilization, (5) quality control, and (6) Mo-100 recovery. To address these issues, a comprehensive technology for cyclotron-production of Tc-99m, developed at the Legnaro National Laboratories of the Italian National Institute of Nuclear Physics (LNL-INFN), will be used as a reference example. Copyright © 2018 Elsevier Ltd. All rights reserved.

Toward organometallic (99m)Tc imaging agents: synthesis of water-stable (99)Tc-NHC complexes.

PubMed

Benz, Michael; Spingler, Bernhard; Alberto, Roger; Braband, Henrik

2013-11-20

(99)Tc(V)O2-NHC complexes containing monodentate and bidentate N-heterocyclic carbenes (NHCs) have been prepared by the reactions of [TcO(glyc)2](-) (glyc = ethyleneglycolato) with 1,3-dimethylimidazoline-2-ylidene (L1), 1,1'-methylene-3,3'-dimethyl-4,4'-diimidazoline-2,2'-diylidene (L2), and 1,1'-methylene-3,3'-diethyl-4,4'-diimidazoline-2,2'-diylidene (L3) in THF. The resulting complexes were fully characterized and their stabilities investigated. While complexes with monodentate NHCs only are hydrolytically unstable, complexes containing bidentate NHCs are water-stable over a broad pH range. The high water stability allows interconversion of the {(99)Tc(V)O2}(+) core into {(99)Tc(V)OCl}(2+) with HCl as the H(+) and Cl(-) source. An alternative procedure to obtain (99)Tc(V)O2-NHC complexes is the in situ deprotonation of imidazolium salts, enabling the preparation of (99)Tc(V)O2-NHC compounds without free NHCs, thus increasing the scope of NHC ligands drastically. The remarkable stability and pH-controllable reactivity of the new complexes underlines the potential of NHCs as stabilizing ligands for (99)Tc complexes and paves the way for the first (99m)Tc-NHC complexes in the future.

Ensemble-based methods for forecasting census in hospital units.

PubMed

Koestler, Devin C; Ombao, Hernando; Bender, Jesse

2013-05-30

The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts.

Improved Anvil Forecasting

NASA Technical Reports Server (NTRS)

Lambert, Winifred C.

2000-01-01

This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

Tc-99m-galactosyl-neoglycoalbumin (Tc-NGA) liver imaging: Potential application in liver transplantation

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

Woodle, E.S.; Vera, D.R.; Ward, R.E.

1984-01-01

Tc-NGA is a hepatocyte receptor-specific imaging agent whose uptake by the liver has been shown to be dependent upon blood flow and receptor concentration. The combination of anatomic and physiologic information obtained with Tc-NGA may provide a new tool for studying hepatic function in liver transplant recipients. To evaluate the potential role of Tc-NGA in liver transplant recipients, studies were performed in four groups of pigs: controls (n=18); common bile duct (CBD) ligation (n=8); orthotopic liver transplant (n=9); and acute hepatic artery ligation (n=1). Serial studies performed in two animals with CBD ligation demonstrated normal imaging anatomy with minor changesmore » in the hepatic time-activity curves when compared to control studies. Studies in liver-transplanted animals showed significant changes in the hepatic time-activity curves during acute rejection and in preservation-related ischemic injury. Tc-NGA also demonstrated focal areas of hepatic infarction in a hepatic allograft within 24 hours of transplantation. The hepatic artery ligation study showed massive changes in the hepatic time-activity curve within two hours after ligation, with a diffuse decrease in hepatic activity. These results indicate that: (1) extrahepatic biliary tract obstruction causes only minor changes in Tc-NGA uptake; (2) Tc-NGA uptake by the liver is very sensitive to acute hepatic ischemia; (3) Tc-NGA may indicate the presence of preservation damage in the early postoperative period; and (4) Tc-NGA hepatic time-activity curves demonstrate significant changes during acute rejection.« less

Forecasts and Warnings of Extreme Solar Storms at the Sun

NASA Astrophysics Data System (ADS)

Lundstedt, H.

2015-12-01

The most pressing space weather forecasts and warnings are those of the most intense solar flares and coronal mass ejections. However, in trying to develop these forecasts and warnings, we are confronted to many fundamental questions. Some of those are: How to define an observable measure for an extreme solar storm? How extreme can a solar storm become and how long is the build up time? How to make forecasts and warnings? Many have contributed to clarifying these general questions. In his presentation we will describe our latest results on the topological complexity of magnetic fields and the use of SDO SHARP parameters. The complexity concept will then be used to discuss the second question. Finally we will describe probability estimates of extreme solar storms.

East Asian winter monsoon forecasting schemes based on the NCEP's climate forecast system

NASA Astrophysics Data System (ADS)

Tian, Baoqiang; Fan, Ke; Yang, Hongqing

2017-12-01

The East Asian winter monsoon (EAWM) is the major climate system in the Northern Hemisphere during boreal winter. In this study, we developed two schemes to improve the forecasting skill of the interannual variability of the EAWM index (EAWMI) using the interannual increment prediction method, also known as the DY method. First, we found that version 2 of the NCEP's Climate Forecast System (CFSv2) showed higher skill in predicting the EAWMI in DY form than not. So, based on the advantage of the DY method, Scheme-I was obtained by adding the EAWMI DY predicted by CFSv2 to the observed EAWMI in the previous year. This scheme showed higher forecasting skill than CFSv2. Specifically, during 1983-2016, the temporal correlation coefficient between the Scheme-I-predicted and observed EAWMI was 0.47, exceeding the 99% significance level, with the root-mean-square error (RMSE) decreased by 12%. The autumn Arctic sea ice and North Pacific sea surface temperature (SST) are two important external forcing factors for the interannual variability of the EAWM. Therefore, a second (hybrid) prediction scheme, Scheme-II, was also developed. This scheme not only involved the EAWMI DY of CFSv2, but also the sea-ice concentration (SIC) observed the previous autumn in the Laptev and East Siberian seas and the temporal coefficients of the third mode of the North Pacific SST in DY form. We found that a negative SIC anomaly in the preceding autumn over the Laptev and the East Siberian seas could lead to a significant enhancement of the Aleutian low and East Asian westerly jet in the following winter. However, the intensity of the winter Siberian high was mainly affected by the third mode of the North Pacific autumn SST. Scheme-I and Scheme-II also showed higher predictive ability for the EAWMI in negative anomaly years compared to CFSv2. More importantly, the improvement in the prediction skill of the EAWMI by the new schemes, especially for Scheme-II, could enhance the forecasting skill of

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

Model-free aftershock forecasts constructed from similar sequences in the past

NASA Astrophysics Data System (ADS)

van der Elst, N.; Page, M. T.

2017-12-01

The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity

Evolving forecasting classifications and applications in health forecasting

PubMed Central

Soyiri, Ireneous N; Reidpath, Daniel D

2012-01-01

Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation. PMID:22615533

An interdisciplinary approach for earthquake modelling and forecasting

NASA Astrophysics Data System (ADS)

Han, P.; Zhuang, J.; Hattori, K.; Ogata, Y.

2016-12-01

Earthquake is one of the most serious disasters, which may cause heavy casualties and economic losses. Especially in the past two decades, huge/mega earthquakes have hit many countries. Effective earthquake forecasting (including time, location, and magnitude) becomes extremely important and urgent. To date, various heuristically derived algorithms have been developed for forecasting earthquakes. Generally, they can be classified into two types: catalog-based approaches and non-catalog-based approaches. Thanks to the rapid development of statistical seismology in the past 30 years, now we are able to evaluate the performances of these earthquake forecast approaches quantitatively. Although a certain amount of precursory information is available in both earthquake catalogs and non-catalog observations, the earthquake forecast is still far from satisfactory. In most case, the precursory phenomena were studied individually. An earthquake model that combines self-exciting and mutually exciting elements was developed by Ogata and Utsu from the Hawkes process. The core idea of this combined model is that the status of the event at present is controlled by the event itself (self-exciting) and all the external factors (mutually exciting) in the past. In essence, the conditional intensity function is a time-varying Poisson process with rate λ(t), which is composed of the background rate, the self-exciting term (the information from past seismic events), and the external excitation term (the information from past non-seismic observations). This model shows us a way to integrate the catalog-based forecast and non-catalog-based forecast. Against this background, we are trying to develop a new earthquake forecast model which combines catalog-based and non-catalog-based approaches.

Forecasting seeing and parameters of long-exposure images by means of ARIMA

NASA Astrophysics Data System (ADS)

Kornilov, Matwey V.

2016-02-01

Atmospheric turbulence is the one of the major limiting factors for ground-based astronomical observations. In this paper, the problem of short-term forecasting seeing is discussed. The real data that were obtained by atmospheric optical turbulence (OT) measurements above Mount Shatdzhatmaz in 2007-2013 have been analysed. Linear auto-regressive integrated moving average (ARIMA) models are used for the forecasting. A new procedure for forecasting the image characteristics of direct astronomical observations (central image intensity, full width at half maximum, radius encircling 80 % of the energy) has been proposed. Probability density functions of the forecast of these quantities are 1.5-2 times thinner than the respective unconditional probability density functions. Overall, this study found that the described technique could adequately describe temporal stochastic variations of the OT power.

Olanzapine induced Q-Tc shortening.

PubMed

Shoja Shafti, Saeed; Fallah Jahromi, Parisa

2014-12-01

Prolongation of Q-Tc interval is commonly accepted as a surrogate marker for the ability of a drug to cause torsade de pointes. In the present study, safety of olanzapine versus risperidone was compared among a group of patients with schizophrenia to see the frequency of the electrocardiographic alterations induced by those atypical antipsychotics. Two hundred and sixty-eight female inpatients with schizophrenia entered in one of the two parallel groups to participate in an open study for random assignment to olanzapine (n = 148) or risperidone (n = 120). Standard 12-lead surface electrocardiogram (ECG) was taken from each patient at baseline, before initiation of treatment, and then at the end of management, just before discharge. The parameters that were assessed included heart rate (HR), P-R interval, QRS interval, Q-T interval (corrected = Q-Tc), ventricular activation time (VAT), ST segment, T wave, axis of QRS, and finally, interventricular conduction process. A total of 37.83% of cases in the olanzapine group and 30% in the risperidone group showed some Q-Tc changes; 13.51% and 24.32% of the patients in the olanzapine group showed prolongation and shortening of the Q-Tc, respectively, while changes in the risperidone group were restricted to only prolongation of Q-Tc. Comparison of means showed a significant increment in Q-Tc by risperidone (p = 0.02). Also, comparison of proportions in the olanzapine group showed significantly more cases with shortening of Q-Tc versus its prolongation (p = 0.01). No significant alterations with respect to other variables were evident. Olanzapine and risperidone had comparable potentiality for induction of Q-Tc changes, while production of further miscellaneous alterations in ECG was more observable in the olanzapine group compared with the risperidone group. Also shortening of Q-Tc was specific to olanzapine.

Ensemble-based methods for forecasting census in hospital units

PubMed Central

2013-01-01

Background The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. Methods In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, we use a seasonality adjusted Poisson Autoregressive (PAR) model where the parameter estimates are obtained via conditional maximum likelihood. The number of daily departures is predicted by modeling the probability of departure from the census using logistic regression models that are adjusted for the amount of time spent in the census and incorporate both patient-specific baseline and time varying patient-specific covariate information. We illustrate our approach using neonatal intensive care unit (NICU) data collected at Women & Infants Hospital, Providence RI, which consists of 1001 consecutive NICU admissions between April 1st 2008 and March 31st 2009. Results Our results demonstrate statistically significant improved prediction accuracy for 3, 5, and 7 day census forecasts and increased precision of our forecasting model compared to a forecasting approach that ignores patient-specific information. Conclusions Forecasting models that utilize patient-specific baseline and time-varying information make the most of data typically available and have the capacity to substantially improve census forecasts. PMID:23721123

Comparative analysis of 99mTc-depreotide and 99mTc-EDDA/HYNIC-TOC thorax scintigrams acquired for the purpose of differential diagnosis of solitary pulmonary nodules.

PubMed

Płachcińska, Anna; Mikołajczak, Renata; Kozak, Józef; Rzeszutek, Katarzyna; Kuśmierek, Jacek

2006-01-01

Aiming at comparison of diagnostic efficacy of 2 radiopharmaceuticals: 99mTc-depreotide (Neospect, Amersham) and 99mTc-EDDA/HYNIC-Tyr3-octreotide (Tektrotyd, Polatom), in differentiation between malignant and benign etiology of solitary pulmonary nodules (SPNs), radionuclide studies with 2 radiotracers were performed in 18 patients. For both radiopharmaceuticals the same acquisition and processing protocols were applied. Studies were acquired with SPECT technique, after administration of 740 MBq of activity. Scintigrams were assessed visually, as: positive (+), equivocal (+/-) and negative (-). Additionally, uptake intensity of both radiotracers in nodules was assessed semiquantitatively, using a tumour-to-background ratio. Verification of scintigraphic results was based in 14 cases upon a pathological examination of tumour samples (histopathology) and in the remaining 4 - on clinical observation and bacteriological studies. Normal scintigrams obtained with both radiopharmaceuticals differed significantly. 99mTc-depreotide was markedly accumulated in spine, sternum, ribs and lungs (mean lung/heart ratio = 2.2). This accumulation was not observed on 99mTc- -EDDA/HYNIC-TOC scintigrams (mean lung/heart ratio = 0.7). In 6 patients a malignant etiology--lung cancer--was revealed (5--adenocarcinoma, 1--squamous cell) and the other 12 cases turned out to be benign (4 hamartomas, 3 tuberculomas, a tuberculous infiltrate, an alien body with inflammatory reaction, a hyperplasia of lymphatic tissue and 2 cases of unknown etiology, from which one had a stable size and the other resolved during a 6 month observation period). In all 6 cases of lung cancer positive results were obtained with both tracers. Moreover, in 2 patients metastases in mediastinum could be observed on scintigrams obtained with both radiopharmaceuticals. From among 12 cases of benign etiology 6 99mTc-depreotide scintigrams were true negative, 1--equivocal and 5--false positive, whereas 6 99mTc

Added value of dynamical downscaling of winter seasonal forecasts over North America

NASA Astrophysics Data System (ADS)

Tefera Diro, Gulilat; Sushama, Laxmi

2017-04-01

Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.

OSSE Evaluation of Prospective Aircraft Reconnaissance Flight Patterns and their Impact on Hurricane Forecasts

NASA Astrophysics Data System (ADS)

Ryan, K. E.; Bucci, L. R.; Christophersen, H.; Atlas, R. M.; Murillo, S.; Dodge, P.

2015-12-01

Each year, NOAA/AOML's Hurricane Research Division (HRD) conducts its Hurricane field Program in which observations are collected via NOAA aircraft to improve the understanding and prediction of hurricanes. Mission experiments suggest a variety of flight patterns and sampling strategies aimed towards their respective goals described by the Intensity Forecasting Experiment (IFEX; Rogers et al., BAMS, 2006, 2013), a collaborative effort among HRD, NHC, and EMC. Evaluating the potential impact of various trade-offs in design is valuable for determining the optimal air reconnaissance flight pattern for a given prospective mission. AOML's HRD has developed a system for performing regional Observing System Simulation Experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasts and analyses. This study focuses on investigating the potential impact of proposed aircraft reconnaissance observing system designs. Aircraft instrument and flight level retrievals were simulated from a regional WRF ARW Nature Run (Nolan et al., 2013) spanning 13 days, covering the life cycle of a rapidly intensifying Atlantic tropical cyclone. The aircraft trajectories are simulated in a variety of ways and are evaluated to investigate the potential impact of aircraft reconnaissance observations on hurricane track and intensity forecasts.

Improvement of High-Resolution Tropical Cyclone Structure and Intensity Forecasts using COAMPS-TC

DTIC Science & Technology

2013-09-30

scientific community including the recent T- PARC /TCS08, ITOP, and HS3 field campaigns to build upon the existing modeling capabilities. We will...heating and cooling rates in developing and non-developing tropical disturbances during tcs-08: radar -equivalent retrievals from mesoscale numerical

Inverse correlation between quasiparticle mass and Tc in a cuprate high-Tc superconductor

PubMed Central

Putzke, Carsten; Malone, Liam; Badoux, Sven; Vignolle, Baptiste; Vignolles, David; Tabis, Wojciech; Walmsley, Philip; Bird, Matthew; Hussey, Nigel E.; Proust, Cyril; Carrington, Antony

2016-01-01

Close to a zero-temperature transition between ordered and disordered electronic phases, quantum fluctuations can lead to a strong enhancement of electron mass and to the emergence of competing phases such as superconductivity. A correlation between the existence of such a quantum phase transition and superconductivity is quite well established in some heavy fermion and iron-based superconductors, and there have been suggestions that high-temperature superconductivity in copper-oxide materials (cuprates) may also be driven by the same mechanism. Close to optimal doping, where the superconducting transition temperature Tc is maximal in cuprates, two different phases are known to compete with superconductivity: a poorly understood pseudogap phase and a charge-ordered phase. Recent experiments have shown a strong increase in quasiparticle mass m* in the cuprate YBa2Cu3O7-δ as optimal doping is approached, suggesting that quantum fluctuations of the charge-ordered phase may be responsible for the high-Tc superconductivity. We have tested the robustness of this correlation between m* and Tc by performing quantum oscillation studies on the stoichiometric compound YBa2Cu4O8 under hydrostatic pressure. In contrast to the results for YBa2Cu3O7-δ, we find that in YBa2Cu4O8, the mass decreases as Tc increases under pressure. This inverse correlation between m* and Tc suggests that quantum fluctuations of the charge order enhance m* but do not enhance Tc. PMID:27034989

Molecular and biochemical characterisation of two aspartic proteinases TcAP1 and TcAP2 from Theobroma cacao seeds.

PubMed

Laloi, Maryse; McCarthy, James; Morandi, Olivia; Gysler, Christof; Bucheli, Peter

2002-09-01

Aspartic proteinase (EC 3.4.23) activity plays a pivotal role in the degradation of Theobroma cacao L. seed proteins during the fermentation step of cacao bean processing. Therefore, this enzyme is believed to be critical for the formation of the peptide and amino acid cocoa flavor precursors that occurs during fermentation. Using cDNA cloning and northern blot analysis, we show here that there are at least two distinct aspartic proteinase genes ( TcAP1 and TcAP2) expressed during cacao seed development. Both genes are expressed early during seed development and their mRNA levels decrease towards the end of seed maturation. TcAP2 is expressed at a much higher level than TcAP1, although the expression of TcAP1 increases slightly during germination. The proteins encoded by TcAP1 and TcAP2 are relatively different from each other (73% identity). This, and the fact that the two corresponding genes have different expression patterns, suggests that the TcAP1 and TcAP2 proteins may have different functions in the maturing seeds and during germination. Because the TcAP2 gene is expressed at a much higher level during seed development than TcAP1, it is likely that the TcAP2 protein is primarily responsible for the majority of the industrially important protein hydrolysis that occurs during cacao bean fermentation. Finally, TcAP2 has been functionally expressed in the yeast Yarrowia lipolytica. The secreted recombinant protein is able to hydrolyse bovine haemoglobin at acidic pH and is sensitive to pepstatin A, confirming that TcAP2 encodes an aspartic proteinase, and strongly suggests that this gene encodes the well-characterized aspartic proteinase of mature cacao seeds.

Effects of FlAsH/Tetracysteine (TC) tag on PrP proteolysis and PrPres formation by TC-scanning

PubMed Central

Taguchi, Yuzuru; Hohsfield, Lindsay A.; Hollister, Jason R.

2014-01-01

The FlAsH/tetracysteine (FlAsH/TC) tag is a powerful tool for fluorescent labeling of proteins. However, even small tags such as FlAsH/TC could alter the behavior of the tagged proteins, especially if the insertion occurs at internal sites. Defining the influence of FlAsH/TC on nearby protein-protein interactions might aid in selecting appropriate positions for internal TC insertions and allow the exploitation of serial FlAsH/TC insertions (TC-scanning) as a probe to characterize sites of protein-protein interaction. To explore this application in the context of substrate-protease interactions, we analyzed the effect of FlAsH/TC insertions on proteolysis of cellular prion protein (PrPsen) in in vitro reactions and generation of the C1 metabolic fragment of PrPsen in live neuroblastoma cells. The influence of FlAsH/TC insertion was evaluated by TC-scanning across the cleavage sites of each protease. The results showed that FlAsH/TC inhibited protease cleavage only within limited ranges of the cleavage sites that varied from about 1 to 6 residues-wide depending on the protease, providing an estimate of the PrP residues interacting with each protease. TC-scanning was also used to probe a different type of protein-protein interaction, the conformational conversion of FlAsH-PrPsen to the prion disease-associated isoform, PrPres. PrP constructs with FlAsH/TC insertions at residues 90–96 but not 97–101 were converted to FlAsH-PrPres, identifying a boundary separating loosely versus compactly folded regions of PrPres. Our observations demonstrate that TC-scanning with the FlAsH/TC tag can be a versatile method for probing protein-protein interactions and folding processes. PMID:23943295

Telecom 2-B and 2-C (TC2B and TC2C)

NASA Technical Reports Server (NTRS)

Dulac, J.; Alvarez, H.

1991-01-01

The DSN (Deep Space Network) mission support requirements for Telecom 2-B and 2-C (TC2B and TC2C) are summarized. These Telecom missions will provide high-speed data link applications, telephone, and television service between France and overseas territories as a follow-on to TC2A. Mission objectives are outlined and the DSN support requirements are defined through the presentation of tables and narratives describing the spacecraft flight profile; DSN support coverage; frequency assignments; support parameters for telemetry, command and support systems; and tracking support responsibility.

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City.

PubMed

Yang, Wan; Olson, Donald R; Shaman, Jeffrey

2016-11-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast.

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City

PubMed Central

2016-01-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast. PMID:27855155

Trypanosoma cruzi diversity in the Gran Chaco: mixed infections and differential host distribution of TcV and TcVI.

PubMed

Monje-Rumi, María M; Brandán, Cecilia Pérez; Ragone, Paula G; Tomasini, Nicolás; Lauthier, Juan J; Alberti D'Amato, Anahí M; Cimino, Rubén O; Orellana, Viviana; Basombrío, Miguel A; Diosque, Patricio

2015-01-01

The transmission cycles of Trypanosoma cruzi in the Gran Chaco are complex networks involving domestic and wild components, whose interrelationships are not well understood. Knowing the circuit of transmission of the different Discrete Typing Units (DTUs) of T. cruzi in the complex environment of the Chaco region is relevant to understanding how the different components (reservoirs, vectors, ecotopes) interact. In the present study we identified the DTUs infecting humans and dogs in two rural areas of the Gran Chaco in Argentina, using molecular methods which avoid parasite culture. Blood samples of humans and dogs were typified by PCR-DNA blotting and hybridization assays with five specific DNA probes (TcI, TcII, TcIII, TcV and TcVI). PCR analyses were performed on seropositive human and dog samples and showed the presence of T. cruzi DNA in 41.7% (98/235) and 53% (35/66) samples, respectively. The identification of infective DTUs was determined in 83.6% (82/98) and 91.4% (32/35) in human and dog samples, respectively. Single infections (36.7% - 36/98) and a previously not detected high proportion of mixed infections (47.9% - 47/98) were found. In a 15.3% (15/98) of samples the infecting DTU was not identified. Among the single infections TcV was the most prevalent DTU (30.6% - 30/98) in human samples; while TcVI (42.8% - 15/35) showed the highest prevalence in dog samples. TcV/TcVI was the most prevalent mixed infection in humans (32.6% - 32/98); and TcI/TcVI (14.3% - 5/35) in dogs. Significant associations between TcV with humans and TcVI with dogs were detected. For the first time, the presence of TcIII was detected in humans from this region. The occurrence of one human infected whit TcIII (a principally wild DTU) could be suggested the emergence of this, in domestic cycles in the Gran Chaco. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Forecasting Skill

DTIC Science & Technology

1981-01-01

for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

Comparison of Tc-99m maraciclatide and Tc-99m sestamibi molecular breast imaging in patients with suspected breast cancer.

PubMed

O'Connor, Michael K; Morrow, Melissa M B; Hunt, Katie N; Boughey, Judy C; Wahner-Roedler, Dietlind L; Conners, Amy Lynn; Rhodes, Deborah J; Hruska, Carrie B

2017-12-01

Molecular breast imaging (MBI) performed with 99m Tc sestamibi has been shown to be a valuable technique for the detection of breast cancer. Alternative radiotracers such as 99m Tc maraciclatide may offer improved uptake in breast lesions. The purpose of this study was to compare relative performance of 99m Tc sestamibi and 99m Tc maraciclatide in patients with suspected breast cancer, using a high-resolution dedicated gamma camera for MBI. Women with breast lesions suspicious for malignancy were recruited to undergo two MBI examinations-one with 99m Tc sestamibi and one with 99m Tc maraciclatide. A radiologist interpreted MBI studies in a randomized, blinded fashion to assign an assessment score (1-5) and measured lesion size. Lesion-to-background (L/B) ratio was measured with region-of-interest analysis. Among 39 analyzable patients, 21 malignant tumors were identified in 21 patients. Eighteen of 21 tumors (86%) were seen on 99m Tc sestamibi MBI and 19 of 21 (90%) were seen on 99m Tc maraciclatide MBI (p = 1). Tumor extent measured with both radiopharmaceuticals correlated strongly with pathologic size ( 99m Tc sestamibi, r = 0.84; 99m Tc maraciclatide, r = 0.81). The L/B ratio in detected breast cancers was similar for the two radiopharmaceuticals: 1.55 ± 0.36 (mean ± S.D.) for 99m Tc sestamibi and 1.62 ± 0.37 (mean ± S.D.) for 99m Tc maraciclatide (p = 0.53). No correlation was found between the L/B ratio and molecular subtype for 99m Tc sestamibi (r s  = 0.12, p = 0.63) or 99m Tc maraciclatide (r s  = -0.12, p = 0.64). Of 20 benign lesions, 10 (50%) were seen on 99m Tc sestamibi and 9 of 20 (45%) were seen on 99m Tc maraciclatide images (p = 0.1). The average L/B ratio for benign lesions was 1.34 ±0.40 (mean ±S.D.) for 99m Tc sestamibi and 1.41 ±0.52 (mean ±S.D.) for 99m Tc maraciclatide (p = 0.75). Overall diagnostic performance was similar for both radiopharmaceuticals. AUC from ROC

Imaging of irradiated liver with Tc-99m-sulfur colloid and Tc-99m-IDA

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

Gelfand, M.J.; Saha, S.; Aron, B.S.

1981-09-01

In three cases, irradiated regions of liver failed to concentrate Tc-99m-sulfur colloid. In two of these three, imaging with Tc-99m-acetanilide iminodiacetic acid (IDA) agents within five days showed near normal hepatic uptake of this hepatobiliary imaging agent. The hepatic parenchymal cells may be imaged with Tc-99m-IDA in some irradiated regions of liver, despite loss of reticuloendothelial cell function.

Amyloidosis of heart and liver: comparison of Tc-99m pyrophosphate and Tc-99m methylene diphosphonate for detection

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

Lee, V.W.; Caldarone, A.G.; Falk, R.H.

1983-07-01

A prospective, comparative study was made of the efficacy of technetium-99m pyrophosphate (Tc PYP) and technetium-99m methylene diphosphonate (Tc MDP) in detecting soft-tissue amyloidois. Tc PYP and Tc MDP scans were obtained within ten-day intervals in seven patients with histologically proven amyloidosis. Tc PYP was a better scanning agent for soft-tissue amyloidosis in all patients. Cardiac and hepatic involvement were proved by autopsy in one patient. Involvement of the heart was confirmed by echocardiography in five patients. The potential use of tc PYP scannning as a screening test for soft-tissue amyloidosis is discussed.

Applicability of plasmid calibrant pTC1507 in quantification of TC1507 maize: an interlaboratory study.

PubMed

Meng, Yanan; Liu, Xin; Wang, Shu; Zhang, Dabing; Yang, Litao

2012-01-11

To enforce the labeling regulations of genetically modified organisms (GMOs), the application of DNA plasmids as calibrants is becoming essential for the practical quantification of GMOs. This study reports the construction of plasmid pTC1507 for a quantification assay of genetically modified (GM) maize TC1507 and the collaborative ring trial in international validation of its applicability as a plasmid calibrant. pTC1507 includes one event-specific sequence of TC1507 maize and one unique sequence of maize endogenous gene zSSIIb. A total of eight GMO detection laboratories worldwide were invited to join the validation process, and test results were returned from all eight participants. Statistical analysis of the returned results showed that real-time PCR assays using pTC1507 as calibrant in both GM event-specific and endogenous gene quantifications had high PCR efficiency (ranging from 0.80 to 1.15) and good linearity (ranging from 0.9921 to 0.9998). In a quantification assay of five blind samples, the bias between the test values and true values ranged from 2.6 to 24.9%. All results indicated that the developed pTC1507 plasmid is applicable for the quantitative analysis of TC1507 maize and can be used as a suitable substitute for dried powder certified reference materials (CRMs).

Do we need demographic data to forecast plant population dynamics?

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Adler, Peter B.

2017-01-01

Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist

Theoretical Modeling of (99)Tc NMR Chemical Shifts.

PubMed

Hall, Gabriel B; Andersen, Amity; Washton, Nancy M; Chatterjee, Sayandev; Levitskaia, Tatiana G

2016-09-06

Technetium-99 (Tc) displays a rich chemistry due to its wide range of accessible oxidation states (from -I to +VII) and ability to form coordination compounds. Determination of Tc speciation in complex mixtures is a major challenge, and (99)Tc nuclear magnetic resonance (NMR) spectroscopy is widely used to probe chemical environments of Tc in odd oxidation states. However, interpretation of (99)Tc NMR data is hindered by the lack of reference compounds. Density functional theory (DFT) calculations can help to fill this gap, but to date few computational studies have focused on (99)Tc NMR of compounds and complexes. This work evaluates the effectiveness of both pure generalized gradient approximation and their corresponding hybrid functionals, both with and without the inclusion of scalar relativistic effects, to model the (99)Tc NMR spectra of Tc(I) carbonyl compounds. With the exception of BLYP, which performed exceptionally well overall, hybrid functionals with inclusion of scalar relativistic effects are found to be necessary to accurately calculate (99)Tc NMR spectra. The computational method developed was used to tentatively assign an experimentally observed (99)Tc NMR peak at -1204 ppm to fac-Tc(CO)3(OH)3(2-). This study examines the effectiveness of DFT computations for interpretation of the (99)Tc NMR spectra of Tc(I) coordination compounds in high salt alkaline solutions.

Interval forecasting of cyber-attacks on industrial control systems

NASA Astrophysics Data System (ADS)

Ivanyo, Y. M.; Krakovsky, Y. M.; Luzgin, A. N.

2018-03-01

At present, cyber-security issues of industrial control systems occupy one of the key niches in a state system of planning and management Functional disruption of these systems via cyber-attacks may lead to emergencies related to loss of life, environmental disasters, major financial and economic damage, or disrupted activities of cities and settlements. There is then an urgent need to develop protection methods against cyber-attacks. This paper studied the results of cyber-attack interval forecasting with a pre-set intensity level of cyber-attacks. Interval forecasting is the forecasting of one interval from two predetermined ones in which a future value of the indicator will be obtained. For this, probability estimates of these events were used. For interval forecasting, a probabilistic neural network with a dynamic updating value of the smoothing parameter was used. A dividing bound of these intervals was determined by a calculation method based on statistical characteristics of the indicator. The number of cyber-attacks per hour that were received through a honeypot from March to September 2013 for the group ‘zeppo-norcal’ was selected as the indicator.

Short-term load forecasting using neural network for future smart grid application

NASA Astrophysics Data System (ADS)

Zennamo, Joseph Anthony, III

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

Ensemble experiments using a nested LETKF system to reproduce intense vortices associated with tornadoes of 6 May 2012 in Japan

NASA Astrophysics Data System (ADS)

Seko, Hiromu; Kunii, Masaru; Yokota, Sho; Tsuyuki, Tadashi; Miyoshi, Takemasa

2015-12-01

Experiments simulating intense vortices associated with tornadoes that occurred on 6 May 2012 on the Kanto Plain, Japan, were performed with a nested local ensemble transform Kalman filter (LETKF) system. Intense vortices were reproduced by downscale experiments with a 12-member ensemble in which the initial conditions were obtained from the nested LETKF system analyses. The downscale experiments successfully generated intense vortices in three regions similar to the observed vortices, whereas only one tornado was reproduced by a deterministic forecast. The intense vorticity of the strongest tornado, which was observed in the southernmost region, was successfully reproduced by 10 of the 12 ensemble members. An examination of the results of the ensemble downscale experiments showed that the duration of intense vorticities tended to be longer when the vertical shear of the horizontal wind was larger and the lower airflow was more humid. Overall, the study results show that ensemble forecasts have the following merits: (1) probabilistic forecasts of the outbreak of intense vortices associated with tornadoes are possible; (2) the miss rate of outbreaks should decrease; and (3) environmental factors favoring outbreaks can be obtained by comparing the multiple possible scenarios of the ensemble forecasts.

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

NASA Astrophysics Data System (ADS)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

The Phosphatidylinositol 3-kinase Class III Complex Containing TcVps15 and TcVps34 Participates in Autophagy in Trypanosoma cruzi.

PubMed

Schoijet, Alejandra C; Sternlieb, Tamara; Alonso, Guillermo D

2017-05-01

Autophagy is a degradative process by which eukaryotic cells digest their own components to provide aminoacids that may function as energy source under nutritional stress conditions. There is experimental evidence for autophagy in parasitic protists belonging to the family Trypanosomatidae. However, few proteins implicated in this process have been characterized so far in these parasites. Moreover, it has been shown that autophagy is involved in Trypanosoma cruzi differentiation and thus might have a role in pathogenicity. Here, we report the cloning and biochemical characterization of TcVps15. In addition, we demonstrate that TcVps15 interact with the PI3K TcVps34 and that both proteins associate with cellular membranes. Under nutritional stress conditions, TcVps15 and TcVps34 modify their subcellular distribution showing a partial co-localization in autophagosomes with TcAtg8.1 and using an active site TcVps15-mutated version (TcVps15-K219D-HA) we demonstrated that this relocalization depends on the TcVps15 catalytic activity. Overexpression of TcVps15-HA and TcVps15-K219D-HA also leads to increased accumulation of monodansylcadaverine (MDC) in autophagic vacuoles under nutritional stress conditions compared to wild-type cells. In addition, the MDC-specific activity shows to be significantly higher in TcVps15-HA overexpressing cells when compared with TcVps15-K219D-HA. Our results reveal for the first time a role of TcVps15 as a key regulator of TcVps34 enzymatic activity and implicate the TcVps15-Vps34 complex in autophagy in T. cruzi, exposing a new key pathway to explore novel chemotherapeutic targets. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Role of upper-ocean on the intensity of Bay of Bengal cyclone `Phailin' as revealed by coupled simulation using Mesoscale Coupled Modeling System (WRF-ROMS)

NASA Astrophysics Data System (ADS)

Mani, B.; Mandal, M.

2016-12-01

Numerical prediction of tropical cyclone (TC) track has improved significantly in recent years, but not the intensity. It is well accepted that TC induced sea surface temperature (SST) cooling in conjunction with pre-existing upper-ocean features have major influences on tropical cyclone intensity. Absence of two-way atmosphere-ocean feedback in the stand-alone atmosphere models has major consequences on their prediction of TC intensity. The present study investigates the role of upper-ocean on prediction of TC intensity and track based on coupled and uncoupled simulation of the Bay of Bengal (BoB) cyclone `Phailin'. The coupled simulation is conducted with the Mesoscale Coupled Modeling System (MCMS) which is a fully coupled atmosphere-ocean modeling system that includes the non-hydrostatic atmospheric model (WRF-ARW) and the three-dimensional hydrostatic ocean model (ROMS). The uncoupled simulation is performed using the atmosphere component of MCMS i.e., the customized version of WRF-ARW for BoB cyclones with prescribed (RTG) SST. The track and intensity of the storm is significantly better simulated by the MCMS and closely followed the observation. The peak intensity, landfall position and time are accurately predicted by MCMS, whereas the uncoupled simulation over predicted the storm intensity. Validation of storm induced SST cooling with the merged microwave-infrared satellite SST indicates that the MCMS simulation shows better correlation both in terms of spatial spread of cold wake and its magnitude. The analysis also suggests that the Pre-existing Cyclonic Eddy (PCE) observed adjacent to the storm enhanced the TC induced SST cooling. It is observed that the response of SST (i.e., cooling) to storm intensity is 12hr with 95% statistical significance. The air-sea enthalpy flux shows a clear asymmetry between Front Left (FL) and Rear Right (RR) regime to the storm center where TC induced cooling is more than 0.5K/24hr. The analysis of atmospheric boundary

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.

OSSE Evaluation of Aircraft Reconnaissance Observations and their Impact on Hurricane Analyses and Forecasts

NASA Astrophysics Data System (ADS)

Ryan, K. E.; Bucci, L. R.; Delgado, J.; Atlas, R. M.; Murillo, S.; Dodge, P.

2016-12-01

NOAA/AOML's Hurricane Research Division (HRD) annually conducts its Hurricane Field Program during which observations are collected via NOAA aircraft to improve the understanding and prediction of hurricanes. Mission experiments suggest a variety of flight patterns and sampling strategies aimed towards their respective goals described by the Intensity Forecasting Experiment (IFEX; Rogers et al., BAMS, 2006, 2013), a collaborative effort among HRD, NHC, and EMC. Evaluating the potential impact of various trade-offs in track design is valuable for determining the optimal air reconnaissance flight pattern for a prospective mission. AOML's HRD has developed a system for performing regional Observing System Simulation Experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasts and analyses. This study focuses on investigating the potential impact of proposed aircraft reconnaissance observing system designs. Aircraft instrument and flight level retrievals were simulated from a regional WRF ARW Nature Run (Nolan et al., 2013) spanning 13 days, covering the life cycle of a rapidly intensifying Atlantic tropical cyclone. The aircraft trajectories of NOAA aircraft are simulated in a variety of ways and are evaluated to examine the potential impact of aircraft reconnaissance observations on hurricane track and intensity forecasts.

99mTc-HYNIC-TOC increased uptake can mimic malignancy in the pancreas uncinate process at somatostatin receptor SPECT/CT.

PubMed

Yamaga, Lilian Yuri Itaya; Neto, Guilherme Campos Carvalho; da Cunha, Marcelo Livorsi; Osawa, Akemi; Oliveira, Julio Cesar Silveira; Fonseca, Ricardo Quartim; Nogueira, Solange Amorim; Wagner, Jairo; Funari, Marcelo Gusmão

2016-03-01

The aim of this study was to assess the occurrence and frequency of increased physiologic uptake of 99mTc-HYNIC-TOC by the uncinate process of the pancreas in SPECT/CT images. Forty-six scans of 41 patients were evaluated retrospectively. The uptake of 99mTc-HYNIC-TOC was considered to be physiologic in patients with normal findings at dedicated abdominal CT or MR and lack of neoplastic lesions in clinical follow-ups. The intensity of uncinate process uptake was compared to the uptake of the normal liver. Focal uptake was attributed to the presence of pancreatic NET in 5 patients. Among the 36 patients without any evidence of malignancy in CT, MR and follow-up, 7 (19.4 %) showed increased uptake in the uncinate process. The intensity of uptake was lesser in 3 (8.3 %), similar in 3 and greater than the normal liver in 1 (2.8 %) case. Increased 99mTc-HYNIC-TOC uptake occurred in 19.4 % of those subjects without any evidence of neuroendocrine tumor in the uncinate process.

In Vitro-Generated Tc17 Cells Present a Memory Phenotype and Serve As a Reservoir of Tc1 Cells In Vivo

PubMed Central

Flores-Santibáñez, Felipe; Cuadra, Bárbara; Fernández, Dominique; Rosemblatt, Mariana V.; Núñez, Sarah; Cruz, Pablo; Gálvez-Cancino, Felipe; Cárdenas, J. César; Lladser, Alvaro; Rosemblatt, Mario; Bono, María Rosa; Sauma, Daniela

2018-01-01

Memory CD8+ T cells are ideal candidates for cancer immunotherapy because they can mediate long-term protection against tumors. However, the therapeutic potential of different in vitro-generated CD8+ T cell effector subsets to persist and become memory cells has not been fully characterized. Type 1 CD8+ T (Tc1) cells produce interferon-γ and are endowed with high cytotoxic capacity, whereas IL-17-producing CD8+ T (Tc17) cells are less cytotoxic but display enhanced self-renewal capacity. We sought to evaluate the functional properties of in vitro-generated Tc17 cells and elucidate their potential to become long lasting memory cells. Our results show that in vitro-generated Tc17 cells display a greater in vivo persistence and expansion in response to secondary antigen stimulation compared to Tc1 cells. When transferred into recipient mice, Tc17 cells persist in secondary lymphoid organs, present a recirculation behavior consistent with central memory T cells, and can shift to a Tc1 phenotype. Accordingly, Tc17 cells are endowed with a higher mitochondrial spare respiratory capacity than Tc1 cells and express higher levels of memory-related molecules than Tc1 cells. Together, these results demonstrate that in vitro-generated Tc17 cells acquire a central memory program and provide a lasting reservoir of Tc1 cells in vivo, thus supporting the use of Tc17 lymphocytes in the design of novel and more effective therapies. PMID:29472932

Asymmetric distribution of convection in tropical cyclones over the western North Pacific Ocean

NASA Astrophysics Data System (ADS)

Yang, Lu; Fei, Jianfang; Huang, Xiaogang; Cheng, Xiaoping; Yang, Xiangrong; Ding, Juli; Shi, Wenli

2016-11-01

Forecasts of the intensity and quantitative precipitation of tropical cyclones (TCs) are generally inaccurate, because the strength and structure of a TC show a complicated spatiotemporal pattern and are affected by various factors. Among these, asymmetric convection plays an important role. This study investigates the asymmetric distribution of convection in TCs over the western North Pacific during the period 2005-2012, based on data obtained from the Feng Yun 2 (FY2) geostationary satellite. The asymmetric distributions of the incidence, intensity and morphology of convections are analyzed. Results show that the PDFs of the convection occurrence curve to the azimuth are sinusoidal. The rear-left quadrant relative to TC motion shows the highest occurrence rate of convection, while the front-right quadrant has the lowest. In terms of intensity, weak convections are favored in the front-left of a TC at large distances, whereas strong convections are more likely to appear to the rear-right of a TC within a 300 km range. More than 70% of all MCSs examined here are elongated systems, and meso- β enlongated convective systems (M βECSs) are the most dominant type observed in the outer region of a TC. Smaller MCSs tend to be more concentrated near the center of a TC. While semi-circular MCSs [M βCCSs, MCCs (mesoscale convective complexes)] show a high incidence rate to the rear of a TC, elongated MCSs [M βECSs, PECSs (persistent elongated convective systems)] are more likely to appear in the rear-right quadrant of a TC within a range of 400 km.

Tc-99m colloid lung uptake in a rare case of toxoplasmosis with liver involvement

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

Garty, I.; Tal, I.; Kaynan, A.

1984-06-01

Intensive lung accumulation of colloid (Tc-99m phytate) was demonstrated in a child suffering from acquired toxoplasmosis with a rare manifestation of severe liver damage. The possible mechanism and clinical importance of colloid lung concentration in this case is briefly discussed, including a review of the literature on this subject.

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.

Track-pattern-based seasonal prediction model for intense tropical cyclone activities over the North Atlantic and the western North Pacific basins

NASA Astrophysics Data System (ADS)

Choi, W.; Ho, C. H.

2015-12-01

Intense tropical cyclones (TCs) accompanying heavy rainfall and destructive wind gusts sometimes cause incredible socio-economic damages in the regions near their landfall. This study aims to analyze intense TC activities in the North Atlantic (NA) and the western North Pacific (WNP) basins and develop their track propensity seasonal prediction model. Considering that the number of TCs in the NA basin is much smaller than that in the WNP basin, different intensity criteria are used; category 1 and above for NA and category 3 and above for WNP based on Saffir-Simpson hurricane wind scale. By using a fuzzy clustering method, intense TC tracks in the NA and the WNP basins are classified into two and three representative patterns, respectively. Each pattern shows empirical relationships with climate variabilities such as sea surface temperature distribution associated with El Niño/La Niña or Atlantic Meridional Mode, Pacific decadal oscillation, upper and low level zonal wind, and strength of subtropical high. The hybrid statistical-dynamical method has been used to develop the seasonal prediction model for each pattern based on statistical relationships between the intense TC activity and seasonal averaged key predictors. The model performance is statistically assessed by cross validation for the training period (1982-2013) and has been applied for the 2014 and 2015 prediction. This study suggests applicability of this model to real prediction work and provide bridgehead of attempt for intense TC prediction.

Vertical distributions of (99)Tc and the (99)Tc/(137)Cs activity ratio in the coastal water off Aomori, Japan.

PubMed

Nakanishi, Takahiro; Zheng, Jian; Aono, Tatsuo; Yamada, Masatoshi; Kusakabe, Masashi

2011-08-01

Using a sector-field ICP-MS the vertical distributions of the (99)Tc concentration and (99)Tc/(137)Cs activity ratio were measured in the coastal waters off Aomori Prefecture, Japan, where a spent-nuclear-fuel reprocessing plant has begun test operation. The (99)Tc concentrations in surface water ranged from 1.8 to 2.4 mBq/m(3), no greater than the estimated background level. Relatively high (99)Tc/(137)Cs activity ratios (10-12 × 10(-4)) would be caused by the inflow of the high-(99)Tc/(137)Cs water mass from the Japan Sea. There is no observable contamination from the reprocessing plant in the investigated area. The (99)Tc concentration and the (99)Tc/(137)Cs activity ratio in water column showed gradual decreases with depth. Our results implied that (99)Tc behaves in a more conservative manner than (137)Cs in marine environments. Copyright © 2011 Elsevier Ltd. All rights reserved.

Differential Activation of CD8+ Tumor-Specific Tc1 and Tc2 Cells by an IL-10-Producing Murine Plasmacytoma

PubMed Central

Pauels, Hans-Gerd; Becker, Christian; Kölsch, Eckehart

1998-01-01

The involvement of counteractive CD8+ T-cell subsets during tumor-specific immune responses was analyzed in a syngeneic murine plasmacytoma model. CD8+ Tc cells against the immunogenic IL-10-producing BALB/c plasmacytoma ADJ-PC-5 can be easily induced by immunization of BALB/c mice with X-irradiated ADJ-PC-5 tumor cells in vivo and in vitro. However, the failure of recipient mice to mount a protective Tc response against the tumor during early stages of a real or simulated tumor growth is not due to immunological ignorance, but depends on the induction of tumor-specific tolerance, involving a population of tumorinduced CD8+ T cells that are able to inhibit the generation of tumor-specific Tc cells in a primary ADJ-PC-5-specific MLTC, using IFN-γ as a suppressive factor. Whereas most longterm cultivated CD8+ ADJ-PC-5-specific Tc lines produce type-1 cytokines on stimulation, at least two of them, which were derived from a primary MLTC, display a type-2 cytokine spectrum. Furthermore, the primary in vitro Tc response against ADJ-PC-5 cells shows characteristics of a Tc2 response. The Tc response is strictly depending on tumor-derived IL-10. CD8+ Tc cells that are induced in a primary MLTC do not produce IFN-γ, and the tumor-specific Tc response is enhanced by IL-4 but suppressed by IFN-γ or IL-12. In contrast, ADJ-PC- 5-specific CD8+ Tc cells from immunized mice are IFN-γ producing Tc1 cells. Since the primary in vitro Tc response against the tumor is suppressed even by the smallest numbers of irradiated ADJ-PC-5-specific Tc1 cells via IFN-γ these Tc1 cells behave similar to the suppressive CD8+ T cells that are induced during early stages of ADJ-PC-5 tumorigenesis. PMID:9814607

Radial-vertical profiles of tropical cyclone derived from dropsondes

NASA Astrophysics Data System (ADS)

Ren, Yifang

The scopes of this thesis research are two folds: the first one is to the construct the intensity-based composite radial-vertical profiles of tropical cyclones (TC) using GPS-based dropsonde observations and the second one is to identify the major deficiencies of Mathur vortices against the dropsonde composites of TCs. The intensity-based dropsonde composites of TCs advances our understanding of the dynamic and thermal structure of TCs of different intensity along the radial direction in and above the boundary layer where lies the devastating high wind that causes property damages and storm surges. The identification of the major deficiencies of Mathur vortices in representing the radial-vertical profiles of TC of different intensity helps to improve numerical predictions of TCs since most operational TC forecast models need to utilize bogus vortices, such as Mathur vortices, to initialize TC forecasts and simulations. We first screen all available GPS dropsonde data within and round 35 named TCs over the tropical Atlantic basin from 1996 to 2010 and pair them with TC parameters derived from the best-track data provided by the National Hurricane Center (NHC) and select 1149 dropsondes that have continuous coverage in the lower troposphere. The composite radial-vertical profiles of tangential wind speed, temperature, mixing ratio and humidity are based for each TC category ranging from "Tropical Storm" (TS) to "Hurricane Category 1" (H1) through "Hurricane Category 5" (H5). The key findings of the dropsonde composites are: (i) all TCs have the maximum tangential wind within 1 km above the ground and a distance of 1-2 times of the radius of maximum wind (RMW) at the surface; (ii) all TCs have a cold ring surrounding the warm core near the boundary layer at a distance of 1-3 times of the RMW and the cold ring structure gradually diminishes at a higher elevation where the warm core structure prevails along the radial direction; (iii) the existence of such shallow cold

Stochastic demographic forecasting.

PubMed

Lee, R D

1992-11-01

"This paper describes a particular approach to stochastic population forecasting, which is implemented for the U.S.A. through 2065. Statistical time series methods are combined with demographic models to produce plausible long run forecasts of vital rates, with probability distributions. The resulting mortality forecasts imply gains in future life expectancy that are roughly twice as large as those forecast by the Office of the Social Security Actuary.... Resulting stochastic forecasts of the elderly population, elderly dependency ratios, and payroll tax rates for health, education and pensions are presented." excerpt

Towards a climatology of tropical cyclone morphometric structures using a newly standardized passive microwave satellite dataset

NASA Astrophysics Data System (ADS)

Cossuth, J.; Hart, R. E.

2013-12-01

The structure of a tropical cyclone (TC) is a spatial representation of its organizational pattern and distribution of energy acquisition and release. Physical processes that react to both the external environment and its own internal dynamics manifest themselves in the TC shape. This structure depicts a specific phase in the TC's meteorological lifecycle, reflecting its past and potentially constraining its future development. For a number of reasons, a thorough objective definition of TC structures and an intercomparison of their varieties have been neglected. This lack of knowledge may be a key reason why TC intensity forecasts, despite numerical model improvements and theoretical advances, have been stagnant in recent years relative to track forecasts. Satellite microwave imagers provide multiple benefits in discerning TC structure, but compiling a research quality data set has been problematic due to several inherent technical and logistical issues. While there are multiple satellite sensors that incorporate microwave frequencies, inter-comparison between such sensors is limited by the different available channels, spatial resolutions, and calibration metrics between satellites, all of which provide inconsistencies in resolving TC structural features. To remedy these difficulties, a global archive of TCs as measured by all available US satellite microwave sensors is compiled and standardized. Using global historical best track data, TC microwave data is retrieved from the Defense Meteorological Satellite Program (DMSP) series (including all SSM/I and SSMIS), TMI, AMSR-E, and WindSat sensors. Standardization between sensors for each TC overpass are performed, including: 1) Recalibration of data from the 'ice scattering' channels to a common frequency (89GHz); 2) Resampling the DMSP series to a higher resolution using the Backus-Gilbert technique; and 3) Re-centering the TC center more precisely using the ARCHER technique (Wimmers and Velden 2010) to analyze the

Intensive culture of black cherry

Treesearch

L.R. Auchmoody

1973-01-01

The recently-released Timber Resources Review forecasts increasing demands for wood and wood products through the end of this century. If these demands are to be met, particularly in view of a shrinking forest-land base, then widespread use of intensive culture must ultimately be adopted. Two cultural techniques being looked at more and more closely as ways of...

Case Studies of Forecasting Ionospheric Total Electron Content

NASA Astrophysics Data System (ADS)

Mannucci, A. J.; Meng, X.; Verkhoglyadova, O. P.; Tsurutani, B.; McGranaghan, R. M.

2017-12-01

We report on medium-range forecast-mode runs of ionosphere-thermosphere coupled models that calculate ionospheric total electron content (TEC), focusing on low-latitude daytime conditions. A medium-range forecast-mode run refers to simulations that are driven by inputs that can be predicted 2-3 days in advance, for example based on simulations of the solar wind. We will present results from a weak geomagnetic storm caused by a high-speed solar wind stream on June 29, 2012. Simulations based on the Global Ionosphere Thermosphere Model (GITM) and the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM) significantly over-estimate TEC in certain low latitude daytime regions, compared to TEC maps based on observations. We will present the results from a more intense coronal mass ejection (CME) driven storm where the simulations are closer to observations. We compare high latitude data sets to model inputs, such as auroral boundary and convection patterns, to assess the degree to which poorly estimated high latitude drivers may be the largest cause of discrepancy between simulations and observations. Our results reveal many factors that can affect the accuracy of forecasts, including the fidelity of empirical models used to estimate high latitude precipitation patterns, or observation proxies for solar EUV spectra, such as the F10.7 index. Implications for forecasts with few-day lead times are discussed

Forecasting production in Liquid Rich Shale plays

NASA Astrophysics Data System (ADS)

Nikfarman, Hanieh

period. In the subsequent Period, dimensionless rate and dimensionless time functions are introduced that help identify transition from initial period into subsequent period. The production trends in terms of the dimensionless parameters converge for a range of rock permeability and stimulation intensity. This helps forecast production beyond transition to the end of life of well. This workflow is applicable to single fluid system.

Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on

Using Multispectral False Color Imaging to Characterize Tropical Cyclone Structure and Environment

NASA Astrophysics Data System (ADS)

Cossuth, J.; Bankert, R.; Richardson, K.; Surratt, M. L.

2016-12-01

The Naval Research Laboratory's (NRL) tropical cyclone (TC) web page (http://www.nrlmry.navy.mil/TC.html) has provided nearly two decades of near real-time access to TC-centric images and products by TC forecasters and enthusiasts around the world. Particularly, microwave imager and sounder information that is featured on this site provides crucial internal storm structure information by allowing users to perceive hydrometeor structure, providing key details beyond cloud top information provided by visible and infrared channels. Towards improving TC analysis techniques and helping advance the utility of the NRL TC webpage resource, new research efforts are presented. This work demonstrates results as well as the methodology used to develop new automated, objective satellite-based TC structure and intensity guidance and enhanced data fusion imagery products that aim to bolster and streamline TC forecast operations. This presentation focuses on the creation and interpretation of false color RGB composite imagery that leverages the different emissive and scattering properties of atmospheric ice, liquid, and vapor water as well as ocean surface roughness as seen by microwave radiometers. Specifically, a combination of near-realtime data and a standardized digital database of global TCs in microwave imagery from 1987-2012 is employed as a climatology of TC structures. The broad range of TC structures, from pinhole eyes through multiple eyewall configurations, is characterized as resolved by passive microwave sensors. The extraction of these characteristic features from historical data also lends itself to statistical analysis. For example, histograms of brightness temperature distributions allows a rigorous examination of how structural features are conveyed in image products, allowing a better representation of colors and breakpoints as they relate to physical features. Such climatological work also suggests steps to better inform the near-real time application of

Rapid shelf‐wide cooling response of a stratified coastal ocean to hurricanes

PubMed Central

Miles, Travis; Xu, Yi; Kohut, Josh; Schofield, Oscar; Glenn, Scott

2017-01-01

Abstract Large uncertainty in the predicted intensity of tropical cyclones (TCs) persists compared to the steadily improving skill in the predicted TC tracks. This intensity uncertainty has its most significant implications in the coastal zone, where TC impacts to populated shorelines are greatest. Recent studies have demonstrated that rapid ahead‐of‐eye‐center cooling of a stratified coastal ocean can have a significant impact on hurricane intensity forecasts. Using observation‐validated, high‐resolution ocean modeling, the stratified coastal ocean cooling processes observed in two U.S. Mid‐Atlantic hurricanes were investigated: Hurricane Irene (2011)—with an inshore Mid‐Atlantic Bight (MAB) track during the late summer stratified coastal ocean season—and Tropical Storm Barry (2007)—with an offshore track during early summer. For both storms, the critical ahead‐of‐eye‐center depth‐averaged force balance across the entire MAB shelf included an onshore wind stress balanced by an offshore pressure gradient. This resulted in onshore surface currents opposing offshore bottom currents that enhanced surface to bottom current shear and turbulent mixing across the thermocline, resulting in the rapid cooling of the surface layer ahead‐of‐eye‐center. Because the same baroclinic and mixing processes occurred for two storms on opposite ends of the track and seasonal stratification envelope, the response appears robust. It will be critical to forecast these processes and their implications for a wide range of future storms using realistic 3‐D coupled atmosphere‐ocean models to lower the uncertainty in predictions of TC intensities and impacts and enable coastal populations to better respond to increasing rapid intensification threats in an era of rising sea levels. PMID:28944132

Rapid shelf-wide cooling response of a stratified coastal ocean to hurricanes.

PubMed

Seroka, Greg; Miles, Travis; Xu, Yi; Kohut, Josh; Schofield, Oscar; Glenn, Scott

2017-06-01

Large uncertainty in the predicted intensity of tropical cyclones (TCs) persists compared to the steadily improving skill in the predicted TC tracks. This intensity uncertainty has its most significant implications in the coastal zone, where TC impacts to populated shorelines are greatest. Recent studies have demonstrated that rapid ahead-of-eye-center cooling of a stratified coastal ocean can have a significant impact on hurricane intensity forecasts. Using observation-validated, high-resolution ocean modeling, the stratified coastal ocean cooling processes observed in two U.S. Mid-Atlantic hurricanes were investigated: Hurricane Irene (2011)-with an inshore Mid-Atlantic Bight (MAB) track during the late summer stratified coastal ocean season-and Tropical Storm Barry (2007)-with an offshore track during early summer. For both storms, the critical ahead-of-eye-center depth-averaged force balance across the entire MAB shelf included an onshore wind stress balanced by an offshore pressure gradient. This resulted in onshore surface currents opposing offshore bottom currents that enhanced surface to bottom current shear and turbulent mixing across the thermocline, resulting in the rapid cooling of the surface layer ahead-of-eye-center. Because the same baroclinic and mixing processes occurred for two storms on opposite ends of the track and seasonal stratification envelope, the response appears robust. It will be critical to forecast these processes and their implications for a wide range of future storms using realistic 3-D coupled atmosphere-ocean models to lower the uncertainty in predictions of TC intensities and impacts and enable coastal populations to better respond to increasing rapid intensification threats in an era of rising sea levels.

Forecasting seasonal influenza with a state-space SIR model

DOE PAGES

Osthus, Dave; Hickmann, Kyle S.; Caragea, Petruţa C.; ...

2017-04-08

Seasonal influenza is a serious public health and societal problem due to its consequences resulting from absenteeism, hospitalizations, and deaths. The overall burden of influenza is captured by the Centers for Disease Control and Prevention’s influenza-like illness network, which provides invaluable information about the current incidence. This information is used to provide decision support regarding prevention and response efforts. Despite the relatively rich surveillance data and the recurrent nature of seasonal influenza, forecasting the timing and intensity of seasonal influenza in the U.S. remains challenging because the form of the disease transmission process is uncertain, the disease dynamics are onlymore » partially observed, and the public health observations are noisy. Fitting a probabilistic state-space model motivated by a deterministic mathematical model [a susceptible-infectious-recovered (SIR) model] is a promising approach for forecasting seasonal influenza while simultaneously accounting for multiple sources of uncertainty. A significant finding of this work is the importance of thoughtfully specifying the prior, as results critically depend on its specification. Our conditionally specified prior allows us to exploit known relationships between latent SIR initial conditions and parameters and functions of surveillance data. We demonstrate advantages of our approach relative to alternatives via a forecasting comparison using several forecast accuracy metrics.« less

Forecasting seasonal influenza with a state-space SIR model

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

Osthus, Dave; Hickmann, Kyle S.; Caragea, Petruţa C.

Seasonal influenza is a serious public health and societal problem due to its consequences resulting from absenteeism, hospitalizations, and deaths. The overall burden of influenza is captured by the Centers for Disease Control and Prevention’s influenza-like illness network, which provides invaluable information about the current incidence. This information is used to provide decision support regarding prevention and response efforts. Despite the relatively rich surveillance data and the recurrent nature of seasonal influenza, forecasting the timing and intensity of seasonal influenza in the U.S. remains challenging because the form of the disease transmission process is uncertain, the disease dynamics are onlymore » partially observed, and the public health observations are noisy. Fitting a probabilistic state-space model motivated by a deterministic mathematical model [a susceptible-infectious-recovered (SIR) model] is a promising approach for forecasting seasonal influenza while simultaneously accounting for multiple sources of uncertainty. A significant finding of this work is the importance of thoughtfully specifying the prior, as results critically depend on its specification. Our conditionally specified prior allows us to exploit known relationships between latent SIR initial conditions and parameters and functions of surveillance data. We demonstrate advantages of our approach relative to alternatives via a forecasting comparison using several forecast accuracy metrics.« less

Forecasting seasonal influenza with a state-space SIR model.

PubMed

Osthus, Dave; Hickmann, Kyle S; Caragea, Petruţa C; Higdon, Dave; Del Valle, Sara Y

2017-03-01

Seasonal influenza is a serious public health and societal problem due to its consequences resulting from absenteeism, hospitalizations, and deaths. The overall burden of influenza is captured by the Centers for Disease Control and Prevention's influenza-like illness network, which provides invaluable information about the current incidence. This information is used to provide decision support regarding prevention and response efforts. Despite the relatively rich surveillance data and the recurrent nature of seasonal influenza, forecasting the timing and intensity of seasonal influenza in the U.S. remains challenging because the form of the disease transmission process is uncertain, the disease dynamics are only partially observed, and the public health observations are noisy. Fitting a probabilistic state-space model motivated by a deterministic mathematical model [a susceptible-infectious-recovered (SIR) model] is a promising approach for forecasting seasonal influenza while simultaneously accounting for multiple sources of uncertainty. A significant finding of this work is the importance of thoughtfully specifying the prior, as results critically depend on its specification. Our conditionally specified prior allows us to exploit known relationships between latent SIR initial conditions and parameters and functions of surveillance data. We demonstrate advantages of our approach relative to alternatives via a forecasting comparison using several forecast accuracy metrics.

Extreme precipitation forecasting in the Chilean Andean region with complex topography using the Weather Research and Forecasting (WRF) model

NASA Astrophysics Data System (ADS)

Gironás, J.; Yáñez Morroni, G.; Caneo, M.; Delgado, R.

2017-12-01

The Weather Research and Forecasting (WRF) model is broadly used for weather forecasting, hindcasting and researching due to its good performance. However, the atmospheric conditions for simulating are not always optimal when it includes complex topographies: affecting WRF mathematical stability and convergence, therefore, its performance. As Chile is a country strongly characterized by a complex topography and high gradients of elevation, WRF is ineffective resolving Chilean mountainous terrain and foothills. The need to own an effective weather forecasting tool relies on that Chile's main cities are located in these regions. Furthermore, the most intense rainfall events take place here, commonly caused by the presence of cutoff lows. This work analyzes a microphysics scheme ensemble to enhance initial forecasts made by the Chilean Weather Agency (DMC). These forecasts were made over the Santiago piedmont, in Quebrada de Ramón watershed, located upstream an urban area highly populated. In this region a non-existing planning increases the potential damage of a flash flood. An initial testing was made over different vertical levels resolution (39 and 50 levels), and subsequently testing with land use and surface models, and finally with the initial and boundary condition data (GFS/FNL). Our task made emphasis in analyzing microphysics and lead time (3 to 5 days before the storm peak) in the computational simulations over three extreme rainfall events between 2015 and 2017. WRF shortcoming are also related to the complex configuration of the synoptic events, even when the steep topography difficult the rainfall event peak amount, and to a lesser degree, the exact rainfall event beginning prediction. No evident trend was found in the lead time, but as expected, better results in rainfall and zero isotherm height are obtained with smaller anticipation. We found that WRF do predict properly the N-hours with the biggest amount of rainfall (5 hours corresponding to

Improved track forecasting of a typhoon reaching landfall from four-dimensional variational data assimilation of AMSU-A retrieved data

NASA Astrophysics Data System (ADS)

Zhao, Ying; Wang, Bin; Ji, Zhongzhen; Liang, Xudong; Deng, Guo; Zhang, Xin

2005-07-01

In this study, an attempt to improve typhoon forecasts is made by incorporating three-dimensional Advanced Microwave Sounding Unit-A (AMSU-A) retrieved wind and temperature and the central sea level pressure of cyclones from typhoon reports or bogus surface low data into initial conditions, on the basis of the Fifth-Generation National Center for Atmospheric Research/Pennsylvania State University Mesoscale Model (MM5) four-dimensional variational data assimilation (4DVar) system with a full-physics adjoint model. All the above-mentioned data are found to be useful for improvement of typhoon forecasts in this mesoscale data assimilation experiment. The comparison tests showed the following results: (1) The assimilation of the satellite-retrieved data was found to have a positive impact on the typhoon track forecast, but the landing position error is ˜150 km. (2) The assimilation of both the satellite-retrieved data and moving information of the typhoon center dramatically improved the track forecast and captured the recurvature and landfall. The mean track error during the 72-hour forecast is 69 km. The predicted typhoon intensity, however, is much weaker than that from observations. (3) The assimilation of both the satellite-retrieved data and the bogus surface low data improved the intensity and track forecasts more significantly than the assimilation of only bogus surface low data (bogus data assimilation) did. The mean errors during the 72-hour forecast are 2.6 hPa for the minimum sea level pressure and 87 km for track position. However, the forecasted landing time is ˜6 hours earlier than the observed one.

Marine Point Forecasts

Science.gov Websites

with smartphones and other mobile platforms new Marine Point Forecasts are a forecast for a specific maps providing zone/point marine forecasts Mobile, AL Eureka, CA San Francisco, CA Los Angeles, CA San

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.

Tc-99m tilmanocept versus Tc-99m sulfur colloid in breast cancer sentinel lymph node identification: Results from a randomized, blinded clinical trial.

PubMed

Unkart, Jonathan T; Hosseini, Ava; Wallace, Anne M

2017-12-01

No prior trials have compared sentinel lymph node (SLN) identification outcomes between Tc-99m tilmanocept (TcTM) and Tc-99m sulfur colloid (TcSC) in breast cancer (BC). We report on the secondary outcomes from a randomized, double-blinded, single surgeon clinical trial comparing post-injection site pain between TcTM and TcSC. Patients were randomized to receive a preoperative single, peritumoral intradermal injection of TcTM or TcSC. The number of total, "hot", and blue nodes detected and removed were compared between groups. Fifty-two (27-TcSC and 25-TcTM) patients were enrolled and underwent definitive surgical treatment. At least one "hot" SLN was detected in all patients. Three (5.8%) patients had a disease positive-SLN. The total number of SLNs removed was 61 (mean 2.26 (standard deviation (SD) 0.90)) in the TcSC group and 54 (mean 2.16 (SD 0.90)) in the TcTM group, P = 0.69. The total number of "hot" nodes in the TcSC group was 1.96 (SD 0.76) compared to 2.04 (SD 0.73) in the TcTM group, P = 0.71. The number of identified SLNs did not differ significantly between TcTM and TcSC. Given that no significant technical advantages exist between the two agents, surgeons should choose a radiopharmaceutical based on cost and side effect profile. © 2017 Wiley Periodicals, Inc.

Imaging experimental intraabdominal abscesses with 99mTc-PEG liposomes and 99mTc-HYNIC IgG.

PubMed Central

Dams, E T; Reijnen, M M; Oyen, W J; Boerman, O C; Laverman, P; Storm, G; van der Meer, J W; Corstens, F H; van Goor, H

1999-01-01

OBJECTIVE: To evaluate the accuracy of technetium-99m-labeled polyethylene glycol-coated liposomes (99mTc-PEG liposomes) and technetium-99m-labeled nonspecific human immunoglobulin G (99mTc-HYNIC IgG) for the scintigraphic detection of experimental intraabdominal abscesses in comparison with that of a standard agent, gallium-67 citrate. BACKGROUND: Scintigraphic imaging techniques can be very useful for the rapid and accurate localization of intraabdominal abscesses. Two newly developed radiolabeled agents, 99mTc-PEG liposomes and 99mTc-HYNIC IgG, have shown to be excellent agents for imaging experimental focal infection, but have not yet been studied in the detection of abdominal abscesses. METHODS: Intraabdominal abscesses were induced in 42 rats using the cecal ligation and puncture technique. Seven days later, randomized groups of rats received 99mTc-PEG liposomes, 99mTc-HYNIC IgG, or 67Ga citrate intravenously. The rats were imaged up to 24 hours after the injection. The biodistribution of the radiolabel was determined by counting dissected tissues ex vivo. Macroscopic intraabdominal abnormalities and focal uptake on the images were independently scored on a semiquantitative scale. RESULTS: 99mTc-PEG liposomes provided the earliest scintigraphic visualization of the abscess (as soon as 2 hours after the injection vs. 4 hours for the other two agents). Liposomes, IgG, and gallium all showed similarly high absolute uptake in the abscess. Focal uptake of liposomes and gallium correlated best with the extent of the macroscopic abnormalities. CONCLUSIONS: 99mTc-PEG liposomes and 99mTc-HYNIC IgG performed at least as well as the standard agent, 67Ga citrate, in the detection of experimental intraabdominal abscesses, with obvious advantages such as lower radiation exposure and more favorable physical properties. Of the two technetium agents, the liposomes seemed to be superior, providing the earliest diagnostic image and the best correlation with the inflammatory

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

Medium Range Forecasts Representation (and Long Range Forecasts?)

NASA Astrophysics Data System (ADS)

Vincendon, J.-C.

2009-09-01

The progress of the numerical forecasts urges us to interest us in more and more distant ranges. We thus supply more and more forecasts with term of some days. Nevertheless, precautions of use are necessary to give the most reliable and the most relevant possible information. Available in a TV bulletin or on quite other support (Internet, mobile phone), the interpretation and the representation of a medium range forecast (5 - 15 days) must be different from those of a short range forecast. Indeed, the "foresee-ability” of a meteorological phenomenon decreases gradually in the course of the ranges, it decreases all the more quickly that the phenomenon is of small scale. So, at the end of some days, the probability character of a forecast becomes very widely dominating. That is why in Meteo-France the forecasts of D+4 to D+7 are accompanied with a confidence index since around ten years. It is a figure between 1 and 5: the more we approach 5, the more the confidence in the supplied forecast is good. In the practice, an indication is supplied for period D+4 / D+5, the other one for period D+6 / D+7, every day being able to benefit from a different forecast, that is be represented in a independent way. We thus supply a global tendency over 24 hours with less and less precise symbols as the range goes away. Concrete examples will be presented. From now on two years, we also publish forecasts to D+8 / J+9, accompanied with a sign of confidence (" good reliability " or " to confirm "). These two days are grouped together on a single map because for us, the described tendency to this term is relevant on a duration about 48 hours with a spatial scale slightly superior to the synoptic scale. So, we avoid producing more than two zones of types of weather over France and we content with giving an evolution for the temperatures (still, in increase or in decline). Newspapers began to publish this information, it should soon be the case of televisions. It is particularly

Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm

PubMed Central

2014-01-01

Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

Fennec dust forecast intercomparison over the Sahara in June 2011

NASA Astrophysics Data System (ADS)

Chaboureau, Jean-Pierre; Flamant, Cyrille; Dauhut, Thibaut; Kocha, Cécile; Lafore, Jean-Philippe; Lavaysse, Chistophe; Marnas, Fabien; Mokhtari, Mohamed; Pelon, Jacques; Reinares Martínez, Irene; Schepanski, Kerstin; Tulet, Pierre

2016-06-01

In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

Fennec dust forecast intercomparison over the Sahara in June 2011

NASA Astrophysics Data System (ADS)

Chaboureau, J. P.; Flamant, C.; Dauhut, T.; Lafore, J. P.; Lavaysse, C.; Pelon, J.; Schepanski, K.; Tulet, P.

2016-12-01

In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynam-ics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

Differential Lung Uptake of 99mTc-HMPAO and 99mTc-Duramycin in the Chronic Hyperoxia Rat Model

PubMed Central

Clough, Anne V.; Audi, Said H.; Haworth, Steven T.; Roerig, David L.

2015-01-01

Noninvasive radionuclide imaging has the potential to identify and assess mechanisms involved in particular stages of lung injury which occur with acute respiratory distress syndrome, for example. Lung uptake of 99mTc-hexamethylpropyleneamine oxime (HMPAO) is reported to be partially dependent on the redox status of the lung tissue while 99mTc-duramycin, a new marker of cell injury, senses cell death via apoptosis and/or necrosis. Thus, we investigated changes in lung uptake of these agents in rat exposed to hyperoxia for prolonged periods, a common model of acute lung injury. Methods Male Sprague-Dawley rats were pre-exposed to either normoxia (21% O2) or hyperoxia (85% O2) for up to 21 days. For imaging, the rats were anesthetized, injected i.v. with either 99mTc-HMPAO or 99mTc-duramycin (37-74 MBq) and planar images were acquired using a high sensitivity modular gamma camera. Subsequently, 99mTc-macroagreggated albumin (37 MBq, diam=10-40 μm) was injected i.v., imaged, and used to define a lung region-of-interest. The lung to background ratio was used as a measure of lung uptake. Results Hyperoxia exposure resulted in a 74% increase in 99mTc-HMPAO lung uptake, which peaked at 7 days and persisted for the 21 days of exposure. 99mTc-duramycin lung uptake was also maximal at 7 days of exposure but decreased to near control levels by 21 days. The sustained elevation of 99mTc-HMPAO uptake suggests ongoing changes in lung redox status whereas cell death appears to have subsided by 21 days. Conclusion These results suggest the potential use of 99mTc-HMPAO and 99mTc-duramycin as redox and cell-death imaging biomarkers, respectively, for in vivo identification and assessment of different stages of lung injury. PMID:23086010

Evaluation of Real-Time Convection-Permitting Precipitation Forecasts in China During the 2013-2014 Summer Season

NASA Astrophysics Data System (ADS)

Zhu, Kefeng; Xue, Ming; Zhou, Bowen; Zhao, Kun; Sun, Zhengqi; Fu, Peiling; Zheng, Yongguang; Zhang, Xiaoling; Meng, Qingtao

2018-01-01

Forecasts at a 4 km convection-permitting resolution over China during the summer season have been produced with the Weather Research and Forecasting model at Nanjing University since 2013. Precipitation forecasts from 2013 to 2014 are evaluated with dense rain gauge observations and compared with operational global model forecasts. Overall, the 4 km forecasts show very good agreement with observations over most parts of China, outperforming global forecasts in terms of spatial distribution, intensity, and diurnal variation. Quantitative evaluations with the Gilbert skill score further confirm the better performance of the 4 km forecasts over global forecasts for heavy precipitation, especially for the thresholds of 100 and 150 mm d-1. Besides bulk characteristics, the representations of some unique features of summer precipitation in China under the influence of the East Asian summer monsoon are further evaluated. These include the northward progression and southward retreat of the main rainband through the summer season, the diurnal variations of precipitation, and the meridional and zonal propagation of precipitation episodes associated with background synoptic flow and the embedded mesoscale convective systems. The 4 km forecast is able to faithfully reproduce most of the features while overprediction of afternoon convection near the southern China coast is found to be a main deficiency that requires further investigations.

Theoretical Modeling of 99 Tc NMR Chemical Shifts

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

Hall, Gabriel B.; Andersen, Amity; Washton, Nancy M.

Technetium (Tc) displays a rich chemistry due to the wide range of oxidation states (from -I to +VII) and ability to form coordination compounds. Determination of Tc speciation in complex mixtures is a major challenge, and 99Tc NMR spec-troscopy is widely used to probe chemical environments of Tc in odd oxidation states. However interpretation of the 99Tc NMR data is hindered by the lack of reference compounds. DFT computations can help fill this gap, but to date few com-putational studies have focused on 99Tc NMR of compounds and complexes. This work systematically evaluates the inclu-sion small percentages of Hartree-Fock exchangemore » correlation and relativistic effects in DFT computations to support in-terpretation of the 99Tc NMR spectra. Hybrid functionals are found to perform better than their pure GGA counterparts, and non-relativistic calculations have been found to generally show a lower mean absolute deviation from experiment. Overall non-relativistic PBE0 and B3PW91 calculations are found to most accurately predict 99Tc NMR chemical shifts.« less

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

Using HPC within an operational forecasting configuration

NASA Astrophysics Data System (ADS)

Jagers, H. R. A.; Genseberger, M.; van den Broek, M. A. F. H.

2012-04-01

Various natural disasters are caused by high-intensity events, for example: extreme rainfall can in a short time cause major damage in river catchments, storms can cause havoc in coastal areas. To assist emergency response teams in operational decisions, it's important to have reliable information and predictions as soon as possible. This starts before the event by providing early warnings about imminent risks and estimated probabilities of possible scenarios. In the context of various applications worldwide, Deltares has developed an open and highly configurable forecasting and early warning system: Delft-FEWS. Finding the right balance between simulation time (and hence prediction lead time) and simulation accuracy and detail is challenging. Model resolution may be crucial to capture certain critical physical processes. Uncertainty in forcing conditions may require running large ensembles of models; data assimilation techniques may require additional ensembles and repeated simulations. The computational demand is steadily increasing and data streams become bigger. Using HPC resources is a logical step; in different settings Delft-FEWS has been configured to take advantage of distributed computational resources available to improve and accelerate the forecasting process (e.g. Montanari et al, 2006). We will illustrate the system by means of a couple of practical applications including the real-time dynamic forecasting of wind driven waves, flow of water, and wave overtopping at dikes of Lake IJssel and neighboring lakes in the center of The Netherlands. Montanari et al., 2006. Development of an ensemble flood forecasting system for the Po river basin, First MAP D-PHASE Scientific Meeting, 6-8 November 2006, Vienna, Austria.

Mental Health and the TC. Chapter 5.

ERIC Educational Resources Information Center

Acampora, Alfonso P., Ed.; Nebelkopf, Ethan, Ed.

This document contains 19 papers from the ninth World Conference of Therapeutic Communities (TCs) that deal with the interface between the mental health establishments and the TC. Papers include: (1) "Psychiatry and the TC" (Jerome Jaffe); (2) "The Chemical Brain" (Sidney Cohen); (3) "Where Does the TC Fail?" (Ab…

Definition of perspective scheme of organization of traffic using methods of forecasting and modeling

NASA Astrophysics Data System (ADS)

Vlasov, V. M.; Novikov, A. N.; Novikov, I. A.; Shevtsova, A. G.

2018-03-01

In the environment of highly developed urban agglomerations, one of the main problems arises - inability of the road network to reach a high level of motorization. The introduction of intelligent transport systems allows solving this problem, but the main issue in their implementation remains open: to what extent this or that method of improving the transport network will be effective and whether it is able to solve the problem of vehicle growth especially for the long-term period. The main goal of this work was the development of an approach to forecasting the increase in the intensity of traffic flow for a long-term period using the population and the level of motorization. The developed approach made it possible to determine the projected population and, taking into account the level of motorization, to determine the growth factor of the traffic flow intensity, which allows calculating the intensity value for a long-term period with high accuracy. The analysis of the main methods for predicting the characteristics of the transport stream is performed. The basic values and parameters necessary for their use are established. The analysis of the urban settlement is carried out and the level of motorization characteristic for the given locality is determined. A new approach to predicting the intensity of the traffic flow has been developed, which makes it possible to predict the change in the transport situation in the long term in high accuracy. Calculations of the magnitude of the intensity increase on the basis of the developed forecasting method are made and the errors in the data obtained are determined. The main recommendations on the use of the developed forecasting approach for the long-term functioning of the road network are formulated.

Forecast Verification: Identification of small changes in weather forecasting skill

NASA Astrophysics Data System (ADS)

Weatherhead, E. C.; Jensen, T. L.

2017-12-01

Global and regonal weather forecasts have improved over the past seven decades most often because of small, incrmental improvements. The identificaiton and verification of forecast improvement due to proposed small changes in forecasting can be expensive and, if not carried out efficiently, can slow progress in forecasting development. This presentation will look at the skill of commonly used verification techniques and show how the ability to detect improvements can depend on the magnitude of the improvement, the number of runs used to test the improvement, the location on the Earth and the statistical techniques used. For continuous variables, such as temperture, wind and humidity, the skill of a forecast can be directly compared using a pair-wise statistical test that accommodates the natural autocorrelation and magnitude of variability. For discrete variables, such as tornado outbreaks, or icing events, the challenges is to reduce the false alarm rate while improving the rate of correctly identifying th discrete event. For both continuus and discrete verification results, proper statistical approaches can reduce the number of runs needed to identify a small improvement in forecasting skill. Verification within the Next Generation Global Prediction System is an important component to the many small decisions needed to make stat-of-the-art improvements to weather forecasting capabilities. The comparison of multiple skill scores with often conflicting results requires not only appropriate testing, but also scientific judgment to assure that the choices are appropriate not only for improvements in today's forecasting capabilities, but allow improvements that will come in the future.

Research on classified real-time flood forecasting framework based on K-means cluster and rough set.

PubMed

Xu, Wei; Peng, Yong

2015-01-01

This research presents a new classified real-time flood forecasting framework. In this framework, historical floods are classified by a K-means cluster according to the spatial and temporal distribution of precipitation, the time variance of precipitation intensity and other hydrological factors. Based on the classified results, a rough set is used to extract the identification rules for real-time flood forecasting. Then, the parameters of different categories within the conceptual hydrological model are calibrated using a genetic algorithm. In real-time forecasting, the corresponding category of parameters is selected for flood forecasting according to the obtained flood information. This research tests the new classified framework on Guanyinge Reservoir and compares the framework with the traditional flood forecasting method. It finds that the performance of the new classified framework is significantly better in terms of accuracy. Furthermore, the framework can be considered in a catchment with fewer historical floods.

An overview of health forecasting.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D

2013-01-01

Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.

Operational hydrological forecasting during the 2 IPHEx-IOP campaign – meet the challenge

USDA-ARS?s Scientific Manuscript database

An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability skill in complex terrain and to investigate the propagation of uncertaint...

(99m)Tc-labeled SWL specific peptide for targeting EphA2 receptor.

PubMed

Liu, Yu; Lan, Xiaoli; Wu, Tao; Lang, Juntao; Jin, Xueyan; Sun, Xun; Wen, Qiong; An, Rui

2014-07-01

EphA2, one member of the Eph receptor family, is widely expressed in multiple aggressive cancers. SWL, a small peptide identified by phage display, has high binding affinity to EphA2, suggesting that it could be exploited for targeted molecular imaging. Therefore, a novel peptide-based probe, (99m)Tc-HYNIC-SWL, was developed and its potential to specifically target EphA2-positive tumors was investigated. The SWL peptide was labeled with hydrazinonicotinic acid (HYNIC), followed by (99m)Tc labeling. Immunofluorescence staining was carried out to detect the expression of EphA2 in A549 lung cancer cells and OCM-1 melanoma cells. Saturation binding experiments were performed by incubating A549 cells with increasing concentrations of radiolabeled peptide in vitro. To test the probe in vivo, nude mice bearing either A549 or OCM-1 derived tumors were established, injected with (99m)Tc-HYNIC-SWL, and subjected to SPECT imaging. Mice injected with excess unlabeled SWL were used as a specific control. Ex vivo γ-counting of dissected tissues from the mice was also performed to evaluate biodistribution. Immunofluorescence staining showed that A549 cells intensively expressed EphA2, while OCM-1 cells had little expression. (99m)Tc-HYNIC-SWL displayed high binding affinity with A549 cells (KD=2.6±0.7nM). From the SPECT images and the results of the biodistribution study, significantly higher uptake of the tracer was seen in A549 tumors (1.44±0.12 %ID/g) than in OCM-1 tumors (0.43±0.20 %ID/g) at 1h after injection. Pre-injection with excess unlabeled peptide in A549-bearing nude mice, significantly reduced tumor uptake of the radiolabeled probe (0.58±0.20 %ID/g) was seen. These data suggest that (99m)Tc-HYNIC-SWL specifically targets EphA2 in tumors. The expression of EphA2 can be noninvasively investigated using (99m)Tc-HYNIC-SWL by SPECT imaging. The in vitro and in vivo characteristics of (99m)Tc-HYNIC-SWL make it a promising probe for EphA2-positive tumor imaging

Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.

PubMed

Joslyn, Susan L; LeClerc, Jared E

2012-03-01

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Forecasting Consumer Adoption of Information Technology and Services--Lessons from Home Video Forecasting.

ERIC Educational Resources Information Center

Klopfenstein, Bruce C.

1989-01-01

Describes research that examined the strengths and weaknesses of technological forecasting methods by analyzing forecasting studies made for home video players. The discussion covers assessments and explications of correct and incorrect forecasting assumptions, and their implications for forecasting the adoption of home information technologies…

Pressure and high-Tc superconductivity in sulfur hydrides.

PubMed

Gor'kov, Lev P; Kresin, Vladimir Z

2016-05-11

The paper discusses fundamentals of record-TC superconductivity discovered under high pressure in sulfur hydride. The rapid increase of TC with pressure in the vicinity of Pcr ≈ 123GPa is interpreted as the fingerprint of a first-order structural transition. Based on the cubic symmetry of the high-TC phase, it is argued that the lower-TC phase has a different periodicity, possibly related to an instability with a commensurate structural vector. In addition to the acoustic branches, the phonon spectrum of H3S contains hydrogen modes with much higher frequencies. Because of the complex spectrum, usual methods of calculating TC are here inapplicable. A modified approach is formulated and shown to provide realistic values for TC and to determine the relative contributions of optical and acoustic branches. The isotope effect (change of TC upon Deuterium for Hydrogen substitution) originates from high frequency phonons and differs in the two phases. The decrease of TC following its maximum in the high-TC phase is a sign of intermixing with pairing at hole-like pockets which arise in the energy spectrum of the cubic phase at the structural transition. On-pockets pairing leads to the appearance of a second gap and is remarkable for its non-adiabatic regime: hydrogen mode frequencies are comparable to the Fermi energy.

Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

2015-04-01

Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

Impeding 99Tc(IV) mobility in novel waste forms

DOE PAGES

Lee, Mal-Soon; Um, Wooyong; Wang, Guohui; ...

2016-06-30

Technetium ( 99Tc) is a long-lived radioactive fission product whose mobility in the subsurface is largely governed by its oxidation state1. Immobilization of Tc in mineral substrates is crucial for radioactive waste management and environmental remediation. Tc(IV) incorporation in spinels2, 3 has been proposed as a novel method to increase Tc retention in glass waste forms. However, experiments with Tc-magnetite under high temperature and oxic conditions showed re-oxidation of Tc(IV) to volatile pertechnetate Tc(VII)O4-.4, 5 Here we address this problem with large-scale ab initio molecular dynamics simulations and propose that elevated temperatures, 1st row transition metal dopants can significantly enhancemore » Tc retention in the order Co > Zn > Ni. Experiments with doped spinels at T=700 ºC provided quantitative confirmation of increased Tc retention in the same order predicted by theory. This work highlights the power of modern state-of-the-art simulations to provide essential insights and generate bottom-up design criteria of complex oxide materials at elevated temperatures.« less

A Global Aerosol Model Forecast for the ACE-Asia Field Experiment

NASA Technical Reports Server (NTRS)

Chin, Mian; Ginoux, Paul; Lucchesi, Robert; Huebert, Barry; Weber, Rodney; Anderson, Tad; Masonis, Sarah; Blomquist, Byron; Bandy, Alan; Thornton, Donald

2003-01-01

We present the results of aerosol forecast during the Aerosol Characterization Experiment (ACE-Asia) field experiment in spring 2001, using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model and the meteorological forecast fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The aerosol model forecast provides direct information on aerosol optical thickness and concentrations, enabling effective flight planning, while feedbacks from measurements constantly evaluate the model, making successful model improvements. We verify the model forecast skill by comparing model predicted total aerosol extinction, dust, sulfate, and SO2 concentrations with those quantities measured by the C-130 aircraft during the ACE-Asia intensive operation period. The GEOS DAS meteorological forecast system shows excellent skills in predicting winds, relative humidity, and temperature for the ACE-Asia experiment area as well as for each individual flight, with skill scores usually above 0.7. The model is also skillful in forecast of pollution aerosols, with most scores above 0.5. The model correctly predicted the dust outbreak events and their trans-Pacific transport, but it constantly missed the high dust concentrations observed in the boundary layer. We attribute this missing dust source to the desertification regions in the Inner Mongolia Province in China, which have developed in recent years but were not included in the model during forecasting. After incorporating the desertification sources, the model is able to reproduce the observed high dust concentrations at low altitudes over the Yellow Sea. Two key elements for a successful aerosol model forecast are correct source locations that determine where the emissions take place, and realistic forecast winds and convection that determine where the aerosols are transported. We demonstrate that our global model can not only account for the large

On the Use of Ocean Dynamic Temperature for Hurricane Intensity Forecasting

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

Balaguru, Karthik; Foltz, Gregory R.; Leung, L. Ruby

Sea surface temperature (SST) and the Tropical Cyclone Heat Potential (TCHP) are metrics used to incorporate the ocean's influence on hurricane intensification in the National Hurricane Center's Statistical Hurricane Intensity Prediction Scheme (SHIPS). While both SST and TCHP serve as useful measures of the upper-ocean heat content, they do not accurately represent ocean stratification effects. Here we show that replacing SST in the SHIPS framework with a dynamic temperature (Tdy), which accounts for the oceanic negative feedback to the hurricane's intensity arising from storm-induced vertical mixing and sea-surface cooling, improves the model performance. While the model with SST and TCHPmore » explains nearly 41% of the variance in 36-hr intensity changes, replacing SST with Tdy increases the variance explained to nearly 44%. Our results suggest that representation of the oceanic feedback, even through relatively simple formulations such as Tdy, may improve the performance of statistical hurricane intensity prediction models such as SHIPS.« less

Socioeconomic Forecasting

DOT National Transportation Integrated Search

2012-05-01

The role of the REMI Policy Insight+ model in socioeconomic forecasting and economic impact analysis of transportation projects was assessed. The REMI : PI+ model is consistent with the state of the practice in forecasting and impact analysis. REMI P...

Socioeconomic forecasting.

DOT National Transportation Integrated Search

2012-05-01

The role of the REMI Policy Insight+ model in socioeconomic forecasting and economic impact analysis of transportation projects was assessed. The REMI : PI+ model is consistent with the state of the practice in forecasting and impact analysis. REMI P...

Extra-tropical Cyclones and Windstorms in Seasonal Forecasts

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Weisheimer, Antje; Knight, Jeff; Thornton, Hazel; Roberts, Julia; Hermanson, Leon

2015-04-01

Severe damages and large insured losses over Europe related to natural phenomena are mostly caused by extra-tropical cyclones and their related windstorm fields. Thus, an adequate representation of these events in seasonal prediction systems and reliable forecasts up to a season in advance would be of high value for society and economy. In this study, state-of-the-art seasonal forecast prediction systems are analysed (ECMWF, UK Met Office) regarding the general climatological representation and the seasonal prediction of extra-tropical cyclones and windstorms during the core winter season (DJF) with a lead time of up to four months. Two different algorithms are used to identify cyclones and windstorm events in these datasets. Firstly, we apply a cyclone identification and tracking algorithm based on the Laplacian of MSLP and secondly, we use an objective wind field tracking algorithm to identify and track continuous areas of extreme high wind speeds (cf. Leckebusch et al., 2008), which can be related to extra-tropical winter cyclones. Thus, for the first time, we can analyse the forecast of severe wind events near to the surface caused by extra-tropical cyclones. First results suggest a successful validation of the spatial climatological distributions of wind storm and cyclone occurrence in the seasonal forecast systems in comparison with reanalysis data (ECMWF-ERA40 & ERAInterim) in general. However, large biases are found for some areas. The skill of the seasonal forecast systems in simulating the year-to-year variability of the frequency of severe windstorm events and cyclones is investigated using the ranked probability skill score. Positive skill is found over large parts of the Northern Hemisphere as well as for the most intense extra-tropical cyclones and its related wind fields.

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

Air Pollution Forecasts: An Overview

PubMed Central

Bai, Lu; Wang, Jianzhou; Lu, Haiyan

2018-01-01

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

Air Pollution Forecasts: An Overview.

PubMed

Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

2018-04-17

Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Initial direct comparison of 99mTc-TOC and 99mTc-TATE in identifying sites of disease in patients with proven GEP NETs.

PubMed

Cwikla, Jaroslaw B; Mikolajczak, Renata; Pawlak, Dariusz; Buscombe, John R; Nasierowska-Guttmejer, Anna; Bator, Andrzej; Maecke, Helmut R; Walecki, Jerzy

2008-07-01

The imaging of neuroendocrine tumors has become one of the most significant areas in nuclear oncology. In an attempt to provide high-quality imaging and possible sensitivity at a reduced cost, time, and radiation dose, several (99m)Tc agents have been proposed. The aim of this initial study was to compare the tumor uptake and biodistribution of 2 new 6-hydrazinopyridine-3-carboxylic acid (HYNIC)-derivatized Tyr(3)-octreotide analogs, (99m)Tc-[HYNIC,Tyr(3)]octreotide ((99m)Tc-TOC) and (99m)Tc-[HYNIC,Tyr(3),Thr(8)]octreotide ((99m)Tc-TATE), in patients with somatostatin receptor-expressing tumors. Each of 12 patients with proven gastrointestinal pancreatic neuroendocrine tumors received a mean activity of 520 MBq of (99m)Tc-TOC and (99m)Tc-TATE. Scintigraphy with both tracers was performed 3-4 h after their injection using standard whole-body and SPECT imaging. The images were reviewed subjectively by 2 readers, who reported tumor uptake lesion by lesion. Both radiotracers demonstrated concordance between the results in 7 patients (58%). In total, 110 sites of disease were identified with (99m)Tc-TOC, compared with 115 with (99m)Tc-TATE. There was 1 case in which (99m)Tc-TOC identified sites of disease not seen on (99m)Tc-TATE imaging but 4 cases in which some sites of disease were seen with (99m)Tc-TATE and not (99m)Tc-TOC. In this initial study, both tracers seem to show similar sites of tumor, with (99m)Tc-TATE having a slight edge in the total number of lesions seen, especially in lymph node metastases.

A prototype system for forecasting landslides in the Seattle, Washington, area

USGS Publications Warehouse

Chleborad, Alan F.; Baum, Rex L.; Godt, Jonathan W.; Powers, Philip S.

2008-01-01

Empirical rainfall thresholds and related information form the basis of a prototype system for forecasting landslides in the Seattle area. The forecasts are tied to four alert levels, and a decision tree guides the use of thresholds to determine the appropriate level. From analysis of historical landslide data, we developed a formula for a cumulative rainfall threshold (CT), P3  =  88.9 − 0.67P15, defined by rainfall amounts in millimeters during consecutive 3 d (72 h) periods, P3, and the 15 d (360 h) period before P3, P15. The variable CT captures more than 90% of historical events of three or more landslides in 1 d and 3 d periods recorded from 1978 to 2003. However, the low probability of landslide occurrence on a day when the CT is exceeded at one or more rain gauges (8.4%) justifies a low-level of alert for possible landslide occurrence, but it does trigger more vigilant monitoring of rainfall and soil wetness. Exceedance of a rainfall intensity-duration threshold I  =  82.73D−1.13, for intensity, I (mm/hr), and duration, D (hr), corresponds to a higher probability of landslide occurrence (30%) and forms the basis for issuing warnings of impending, widespread occurrence of landslides. Information about the area of exceedance and soil wetness can be used to increase the certainty of landslide forecasts (probabilities as great as 71%). Automated analysis of real-time rainfall and subsurface water data and digital quantitative precipitation forecasts are needed to fully implement a warning system based on the two thresholds.

Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle; Zavodsky, Bradley

2011-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model

99mTc-3P4-RGD2 Scintimammography in the Assessment of Breast Lesions: Comparative Study with 99mTc-MIBI

PubMed Central

Gao, Shi; Ji, Tiefeng; Wen, Qiang; Song, Yan; Zhu, Lei; Xu, Zheli; Liu, Lin

2014-01-01

Purpose To compare the potential application of 99mTc-3P-Arg-Gly-Asp (99mTc-3P4-RGD2) scintimammography (SMM) and 99mTc-methoxyisobutylisonitrile (99mTc-MIBI) SMM for the differentiation of malignant from benign breast lesions. Method Thirty-six patients with breast masses on physical examination and/or suspicious mammography results that required fine needle aspiration cytology biopsy (FNAB) were included in the study. 99mTc-3P4-RGD2 and 99mTc-MIBI SMM were performed with single photon emission computed tomography (SPECT) at 60 min and 20 min respectively after intravenous injection of 738±86 MBq radiotracers on a separate day. Images were evaluated by the tumor to non-tumor localization ratios (T/NT). Receiver operating characteristic (ROC) curve analysis was performed on each radiotracer to calculate the cut-off values of quantitative indices and to compare the diagnostic performance for the ability to differentiate malignant from benign diseases. Results The mean T/NT ratio of 99mTc-3P4-RGD2 in malignant lesions was significantly higher than that in benign lesions (3.54±1.51 vs. 1.83±0.98, p<0.001). The sensitivity, specificity, and accuracy of 99mTc-3P4-RGD2 SMM were 89.3%, 90.9% and 89.7%, respectively, with a T/NT cut-off value of 2.40. The mean T/NT ratio of 99mTc-MIBI in malignant lesions was also significantly higher than that in benign lesions (2.86±0.99 vs. 1.51±0.61, p<0.001). The sensitivity, specificity and accuracy of 99mTc-MIBI SMM were 87.5%, 72.7% and 82.1%, respectively, with a T/NT cut-off value of 1.45. According to the ROC analysis, the area under the curve for 99mTc-3P4-RGD2 SMM (area = 0.851) was higher than that for 99mTc-MIBI SMM (area = 0.781), but the statistical difference was not significant. Conclusion 99mTc-3P4-RGD2 SMM does not provide any significant advantage over the established 99mTc-MIBI SMM for the detection of primary breast cancer. The T/NT ratio of 99mTc-3P4-RGD2 SMM was significantly higher than that of 99mTc

Analysis of accumulation of 99mTc-octreotide and 99mTc-EDDA/HYNIC-Tyr3-octreotide in the rat kidneys.

PubMed

Kopecky, Martin; Semecky, Vladimir; Trejtnar, Frantisek; Laznicek, Milan; Laznickova, Alice; Nachtigal, Petr; Decristoforo, Clemens; Mather, Stephen J; Mäcke, Helmut R

2004-02-01

The aim of this study was to compare renal handling and distribution of (99m)Tc-octreotide and (99m)Tc-EDDA/HYNIC-Tyr(3)-octreotide (HYNIC-TOC) in rats. In kidney perfusion experiments, the renal clearance value of (99m)Tc-octreotide was three times lower than that of (99m)Tc-EDDA/HYNIC-TOC. The predominant renal excretion of (99m)Tc-EDDA/HYNIC-TOC was associated with a high and long-term renal accumulation up to 48 hrs. Microautoradiographic results indicated that (99m)Tc-EDDA/HYNIC-TOC was retained mainly in the renal medulla within the cells of the collecting ducts and in the surrounding tissue. Lower positivity was found in the proximal and distal tubular cells. We conclude that the mechanism of renal accumulation of somatostatin analogues renal accumulation is complex and that proximal tubular reabsorption is probably not the main mechanism for uptake of (99m)Tc-EDDA/HYNIC-TOC in the kidneys. The presence of the somatostatin receptors, differences in the tonicity level within kidneys and other possible mechanisms could participate in their renal accumulation.

Novel 99mTc(III)-azide complexes [99mTc(N3)(CDO)(CDOH)2B-R] (CDOH2=cyclohexanedione dioxime) as potential radiotracers for heart imaging.

PubMed

Liu, Min; Zheng, Yumin; Avcibasi, Ugur; Liu, Shuang

2016-11-01

In this study, novel 99m Tc(III)-azide complexes [ 99m Tc(N 3 )(CDO)(CDOH) 2 B-R] ( 99m Tc-ISboroxime-N 3 : R=IS; 99m Tc-MPboroxime-N 3 : R=MP; 99m Tc-PAboroxime-N 3 : R=PA; 99m Tc-PYboroxime-N 3 : R=PY; and 99m Tc-Uboroxime-N 3 : R=5U) were evaluated as heart imaging agents. Complexes [ 99m Tc(N 3 )(CDO)(CDOH) 2 B-R] (R=IS, MP, PA, PY and 5U) were prepared by ligand exchange between NaN 3 and [ 99m TcCl(CDO)(CDOH) 2 B-R]. Biodistribution and imaging studies were carried out in Sprague-Dawley rats. Image quantification was performed to compare their initial heart uptake and myocardial retention. 99m Tc-ISboroxime-N 3 , 99m Tc-PYboroxime-N 3 and 99m Tc-Uboroxime-N 3 were prepared with high RCP (93-98%) while the RCP of 99m Tc-MPboroxime-N 3 and 99m Tc-PAboroxime-N 3 was 80-85%. The myocardial retention curves of 99m Tc-ISboroxime-N 3 , 99m Tc-PYboroxime-N 3 and 99m Tc-Uboroxime-N 3 were best fitted to the bi-exponential decay function. The half-time of the fast component was 1.6±0.4min for 99m Tc-ISboroxime-N 3 , 0.7±0.1min for 99m Tc-PYboroxime-N 3 and 0.9±0.4min for 99m Tc-Uboroxime-N 3 . The 2-min heart uptake from biodistribution studies followed the ranking order of 99m Tc-ISboroxime-N 3 (3.60±0.68%ID/g)> 99m Tc-PYboroxime-N 3 (2.35±0.37%ID/g)≫ 99m Tc-Uboroxime-N 3 (1.29±0.06%ID/g). 99m Tc-ISboroxime-N 3 had the highest 2-min heart uptake among 99m Tc radiotracers revaluated in SD rats. High quality SPECT images were obtained with the right and left ventricular walls being clearly delineated. The best image acquisition window was 0-5min for 99m Tc-ISboroxime-N 3 . Both azide coligand and boronate caps had significant impact on the heart uptake and myocardial retention of complexes [ 99m Tc(N 3 )(CDO)(CDOH) 2 B-R]. Among the radiotracers evaluated in SD rats, 99m Tc-ISboroxime-N 3 has the highest initial heart uptake with the heart retention comparable to that of 99m Tc-Teboroxime. 99m Tc-ISboroxime-N 3 is a promising alternative to 99m Tc-Teboroxime for

Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

2017-08-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

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

Coupled Atmosphere-Wave-Ocean Modeling of Tropical Cyclones: Progress, Challenges, and Ways Forward

NASA Astrophysics Data System (ADS)

Chen, Shuyi

2015-04-01

/s. It is found that the air-sea fluxes are quite asymmetric around a storm with complex features representing various air-sea interaction processes in TCs. A unique observation in Typhoon Fanapi is the development of a stable boundary layer in the near-storm cold wake region, which has a direct impact on TC inner core structure and intensity. Despite of the progress, challenges remain. Air-sea momentum exchange in wind speed greater than 30-40 m/s is largely unresolved. Directional wind-wave stress and wave-current stress are difficult to determine from observations. Effects of sea spray on the air-sea fluxes are still not well understood. This talk will provide an overview on progress made in recent years, challenges we are facing, and ways forward. An integrated coupled observational and atmosphere-wave-ocean modeling system is urgently needed, in which coupled model development and targeted observations from field campaign and lab measurements together form the core of the research and prediction system. Another important aspect is that fully coupled models provide explicit, integrated impact forecasts of wind, rain, waves, ocean currents and surges in TCs and winter storms, which are missing in most current NWP models. It requires a new strategy for model development, evaluation, and verification. Ensemble forecasts using high-resolution coupled atmosphere-wave-ocean models can provide probabilistic forecasts and quantitative uncertainty estimates, which also allow us to explore new methodologies to verify probabilistic impact forecasts and evaluate model physics using a stochastic approach. Examples of such approach in TCs including Superstorm Sandy will be presented.

Medium-range fire weather forecasts

Treesearch

J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

1991-01-01

The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

WPC Maximum Heat Index Forecasts

Science.gov Websites

Forecasts for Western US CLICK ON MAPS FOR MAXIMUM HEAT INDEX AND PROBABILITY FORECASTS FROM SUN MAY 27 2018 02 CLICK to view SAT JUN 02 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN

The Tribolium chitin synthase genes TcCHS1 and TcCHS2 are specialized for synthesis of epidermal cuticle and midgut peritrophic matrix.

PubMed

Arakane, Y; Muthukrishnan, S; Kramer, K J; Specht, C A; Tomoyasu, Y; Lorenzen, M D; Kanost, M; Beeman, R W

2005-10-01

Functional analysis of the two chitin synthase genes, TcCHS1 and TcCHS2, in the red flour beetle, Tribolium castaneum, revealed unique and complementary roles for each gene. TcCHS1-specific RNA interference (RNAi) disrupted all three types of moult (larval-larval, larval-pupal and pupal-adult) and greatly reduced whole-body chitin content. Exon-specific RNAi showed that splice variant 8a of TcCHS1 was required for both the larval-pupal and pupal-adult moults, whereas splice variant 8b was required only for the latter. TcCHS2-specific RNAi had no effect on metamorphosis or on total body chitin content. However, RNAi-mediated down-regulation of TcCHS2, but not TcCHS1, led to cessation of feeding, a dramatic shrinkage in larval size and reduced chitin content in the midgut.

An impact analysis of forecasting methods and forecasting parameters on bullwhip effect

NASA Astrophysics Data System (ADS)

Silitonga, R. Y. H.; Jelly, N.

2018-04-01

Bullwhip effect is an increase of variance of demand fluctuation from downstream to upstream of supply chain. Forecasting methods and forecasting parameters were recognized as some factors that affect bullwhip phenomena. To study these factors, we can develop simulations. There are several ways to simulate bullwhip effect in previous studies, such as mathematical equation modelling, information control modelling, computer program, and many more. In this study a spreadsheet program named Bullwhip Explorer was used to simulate bullwhip effect. Several scenarios were developed to show the change in bullwhip effect ratio because of the difference in forecasting methods and forecasting parameters. Forecasting methods used were mean demand, moving average, exponential smoothing, demand signalling, and minimum expected mean squared error. Forecasting parameters were moving average period, smoothing parameter, signalling factor, and safety stock factor. It showed that decreasing moving average period, increasing smoothing parameter, increasing signalling factor can create bigger bullwhip effect ratio. Meanwhile, safety stock factor had no impact to bullwhip effect.

Assessment of the direct cyclotron production of (99m)Tc: An approach to crisis management of (99m)Tc shortage.

PubMed

Rovais, Mohammad Reza Aboudzadeh; Aardaneh, Khosro; Aslani, Gholamreza; Rahiminejad, Ali; Yousefi, Kamran; Boulouri, Fatemeh

2016-06-01

Nowadays, the cyclotron production of technetium-99m ((99m)Tc) has been increased, due to the worldwide (99m)Tc generator shortage. In the present work, an improved strategy for the production of (99m)Tc, using the proton irradiation of the enriched (100)Mo was developed. The performance of this method in terms of the production yield, chemical purity, radiochemical purity, as well as radionuclide purity was evaluated. The average production yield was measured to be 356MBqμA(-1)h(-1). A good agreement was found between the calculated production yield and the experimental one. The radiochemical separation and total recovery yields of (99m)Tc were 92% and 69%, respectively. The radiochemical and the radionuclide purities of the (99m)Tc were 99% and >99.99% at the end of purification, respectively. The results of quality control tests (QC) support the concept that cyclotron-produced (99m)Tc is suitable for preparation of USP-compliant. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of wintertime precipitation forecasts over the Australian Snowy Mountains

NASA Astrophysics Data System (ADS)

Huang, Yi; Chubb, Thomas; Sarmadi, Fahimeh; Siems, Steven T.; Manton, Michael J.; Franklin, Charmaine N.; Ebert, Elizabeth

2018-07-01

This study evaluates the Australian Community Climate and Earth-System Simulator (ACCESS) Numerical Weather Prediction system in forecasting precipitation across the Australian Snowy Mountains for two cool seasons. Metrics based on seasonal accumulated and daily precipitation show that the model is able to reproduce the observed domain-mean accumulated precipitation reasonably well (with a slight overestimation), but this is, in part, due to a compensation of various errors. Both the frequency and intensity of the heavy precipitation days (domain-mean daily precipitation >5 mm day-1) are overrepresented, particularly over the complex terrain and high-elevation areas, whereas the frequency of the very light precipitation days (domain-mean daily precipitation <1 mm day-1) is underestimated, primarily over lower-elevation areas both upwind and downwind of the mountains. Most of the precipitation is forecasted by the grid-scale precipitation scheme, with appreciable snowfalls predicted over the high elevations. The model also demonstrates appreciable skill in reproducing the synoptic regimes. The proportion of the forecast precipitation for each regime is comparable to the observations, although the orographic enhancement over the western slopes of the mountains is more pronounced in the forecasts, particularly for the wetter regimes. An examination on the effect of the lower-atmosphere stability suggests that most of the precipitation (50-70% over the high elevations) is produced under the "unblocked" condition, which is diagnosed 31% of the time. The remainder is produced under the "blocked" condition. Combined with a case study, potential sources of error associated with the forecast precipitation biases are also discussed.

Measuring functioning hepatocytes using Tc-99m galactosylneoglycoalbumin (Tc-NGA)

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

Stadalnik, R.C.; Vera, D.R.; Quadro, R.E.

1984-01-01

Tc-NGA is a synthetic ligand which binds only to hepatic binding protein (HBP), a receptor found only in the liver. It exhibits the properties of high tissue specificity, affinity-dependent uptake, and dose-dependent uptake. Tc-NGA provides an opportunity to study the functioning hepatocyte. The authors evaluated the usefulness of this technique in patients with hepatitis and hepatoma. After intravenous administration of 5 mCi Tc-NGA, dynamic images were acquired for 30 minutes followed by static views. Estimates of HBP concentrations were obtained by kinetic analysis of blood and liver time-activity curves. Kinetic estimates (reduced chi-squares < 3.0) of HBP correlated well withmore » the clinical course and histology. For example, a patient with hepatoma whose calculated receptor population (functioning hepatocytes) was 3.0 +- 0.9 x 10/sup -7/ mole, which is the normal range, is doing well undergoing chemotherapy. Liver biopsy demonstrated normal liver tissue except for the hepatoma. Another patient with hepatoma who had a severely depressed receptor population, 1.2 +- 0.2 x 10/sup -8/ mole, expired one week after the study. Liver biopsy demonstrated practically no normal tissue. Thus, by means of a complementary, receptor radiopharmaceutical and mathematical model, one should be able to quantitatively follow hepatocyte function and predict response to a therapeutic regimen.« less

Blending forest fire smoke forecasts with observed data can improve their utility for public health applications

NASA Astrophysics Data System (ADS)

Yuchi, Weiran; Yao, Jiayun; McLean, Kathleen E.; Stull, Roland; Pavlovic, Radenko; Davignon, Didier; Moran, Michael D.; Henderson, Sarah B.

2016-11-01

Fine particulate matter (PM2.5) generated by forest fires has been associated with a wide range of adverse health outcomes, including exacerbation of respiratory diseases and increased risk of mortality. Due to the unpredictable nature of forest fires, it is challenging for public health authorities to reliably evaluate the magnitude and duration of potential exposures before they occur. Smoke forecasting tools are a promising development from the public health perspective, but their widespread adoption is limited by their inherent uncertainties. Observed measurements from air quality monitoring networks and remote sensing platforms are more reliable, but they are inherently retrospective. It would be ideal to reduce the uncertainty in smoke forecasts by integrating any available observations. This study takes spatially resolved PM2.5 estimates from an empirical model that integrates air quality measurements with satellite data, and averages them with PM2.5 predictions from two smoke forecasting systems. Two different indicators of population respiratory health are then used to evaluate whether the blending improved the utility of the smoke forecasts. Among a total of six models, including two single forecasts and four blended forecasts, the blended estimates always performed better than the forecast values alone. Integrating measured observations into smoke forecasts could improve public health preparedness for smoke events, which are becoming more frequent and intense as the climate changes.

Discordant hepatic uptake between Tc-99m sulfur colloid and Tc-99m DISIDA in hypervitaminosis A

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

Vincent, L.M.; McCartney, W.H.; Mauro, M.A.

1984-02-01

Scintigraphic findings in a patient with biopsy-proven hypervitaminosis A included markedly impaired hepatic uptake of Tc-99m sulfur colloid but essentially normal uptake of Tc-99m DISIDA. This case presents a potential cause for image discordance with these two agents.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

NASA Astrophysics Data System (ADS)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET

[Medical human resources planning in Europe: A literature review of the forecasting models].

PubMed

Benahmed, N; Deliège, D; De Wever, A; Pirson, M

2018-02-01

Healthcare is a labor-intensive sector in which half of the expenses are dedicated to human resources. Therefore, policy makers, at national and internal levels, attend to the number of practicing professionals and the skill mix. This paper aims to analyze the European forecasting model for supply and demand of physicians. To describe the forecasting tools used for physician planning in Europe, a grey literature search was done in the OECD, WHO, and European Union libraries. Electronic databases such as Pubmed, Medine, Embase and Econlit were also searched. Quantitative methods for forecasting medical supply rely mainly on stock-and-flow simulations and less often on systemic dynamics. Parameters included in forecasting models exhibit wide variability for data availability and quality. The forecasting of physician needs is limited to healthcare consumption and rarely considers overall needs and service targets. Besides quantitative methods, horizon scanning enables an evaluation of the changes in supply and demand in an uncertain future based on qualitative techniques such as semi-structured interviews, Delphi Panels, or focus groups. Finally, supply and demand forecasting models should be regularly updated. Moreover, post-hoc analyze is also needed but too rarely implemented. Medical human resource planning in Europe is inconsistent. Political implementation of the results of forecasting projections is essential to insure efficient planning. However, crucial elements such as mobility data between Member States are poorly understood, impairing medical supply regulation policies. These policies are commonly limited to training regulations, while horizontal and vertical substitution is less frequently taken into consideration. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Fishing Forecasts

NASA Technical Reports Server (NTRS)

1988-01-01

ROFFS stands for Roffer's Ocean Fishing Forecasting Service, Inc. Roffer combines satellite and computer technology with oceanographic information from several sources to produce frequently updated charts sometimes as often as 30 times a day showing clues to the location of marlin, sailfish, tuna, swordfish and a variety of other types. Also provides customized forecasts for racing boats and the shipping industry along with seasonal forecasts that allow the marine industry to formulate fishing strategies based on foreknowledge of the arrival and departure times of different fish. Roffs service exemplifies the potential for benefits to marine industries from satellite observations. Most notable results are reduced search time and substantial fuel savings.

A simple Lagrangian forecast system with aviation forecast potential

NASA Technical Reports Server (NTRS)

Petersen, R. A.; Homan, J. H.

1983-01-01

A trajectory forecast procedure is developed which uses geopotential tendency fields obtained from a simple, multiple layer, potential vorticity conservative isentropic model. This model can objectively account for short-term advective changes in the mass field when combined with fine-scale initial analyses. This procedure for producing short-term, upper-tropospheric trajectory forecasts employs a combination of a detailed objective analysis technique, an efficient mass advection model, and a diagnostically proven trajectory algorithm, none of which require extensive computer resources. Results of initial tests are presented, which indicate an exceptionally good agreement for trajectory paths entering the jet stream and passing through an intensifying trough. It is concluded that this technique not only has potential for aiding in route determination, fuel use estimation, and clear air turbulence detection, but also provides an example of the types of short range forecasting procedures which can be applied at local forecast centers using simple algorithms and a minimum of computer resources.

Impeding 99Tc(IV) mobility in novel waste forms

PubMed Central

Lee, Mal-Soon; Um, Wooyong; Wang, Guohui; Kruger, Albert A.; Lukens, Wayne W.; Rousseau, Roger; Glezakou, Vassiliki-Alexandra

2016-01-01

Technetium (99Tc) is an abundant, long-lived radioactive fission product whose mobility in the subsurface is largely governed by its oxidation state. Tc immobilization is crucial for radioactive waste management and environmental remediation. Tc(IV) incorporation in spinels has been proposed as a novel method to increase Tc retention in glass waste forms during vitrification. However, experiments under high-temperature and oxic conditions show reoxidation of Tc(IV) to volatile pertechnetate, Tc(VII). Here we examine this problem with ab initio molecular dynamics simulations and propose that, at elevated temperatures, doping with first row transition metal can significantly enhance Tc retention in magnetite in the order Co>Zn>Ni. Experiments with doped spinels at 700 °C provide quantitative confirmation of the theoretical predictions in the same order. This work highlights the power of modern, state-of-the-art simulations to provide essential insights and generate theory-inspired design criteria of complex materials at elevated temperatures. PMID:27357121

Forecasting asthma-related hospital admissions in London using negative binomial models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-05-01

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

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

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.

EnrollForecast for Excel: K-12 Enrollment Forecasting Program. Software & User's Guide. [Computer Diskette].

ERIC Educational Resources Information Center

Smith, Curtis A.

"EnrollForecast for Excel" will generate a 5-year forecast of K-12 student enrollment. It will also work for any combination of grades between kindergarten and twelth. The forecasts can be printed as either a table or a graph. The user must provide birth history (only if forecasting kindergarten) and enrollment history information. The user also…

Development of a Luminex Bead Based Assay for Diagnosis of Toxocariasis Using Recombinant Antigens Tc-CTL-1 and Tc-TES-26.

PubMed

Anderson, John P; Rascoe, Lisa N; Levert, Keith; Chastain, Holly M; Reed, Matthew S; Rivera, Hilda N; McAuliffe, Isabel; Zhan, Bin; Wiegand, Ryan E; Hotez, Peter J; Wilkins, Patricia P; Pohl, Jan; Handali, Sukwan

2015-01-01

The clinical spectrum of human disease caused by the roundworms Toxocara canis and Toxocara cati ranges from visceral and ocular larva migrans to covert toxocariasis. The parasite is not typically recovered in affected tissues, so detection of parasite-specific antibodies is usually necessary for establishing a diagnosis. The most reliable immunodiagnostic methods use the Toxocara excretory-secretory antigens (TES-Ag) in ELISA formats to detect Toxocara-specific antibodies. To eliminate the need for native parasite materials, we identified and purified immunodiagnostic antigens using 2D gel electrophoresis followed by electrospray ionization mass spectrometry. Three predominant immunoreactive proteins were found in the TES; all three had been previously described in the literature: Tc-CTL-1, Tc-TES-26, and Tc-MUC-3. We generated Escherichia coli expressed recombinant proteins for evaluation in Luminex based immunoassays. We were unable to produce a functional assay with the Tc-MUC-3 recombinant protein. Tc-CTL-1 and Tc-TES-26 were successfully coupled and tested using defined serum batteries. The use of both proteins together generated better results than if the proteins were used individually. The sensitivity and specificity of the assay for detecting visceral larval migrans using Tc-CTL-1 plus Tc-TES-26 was 99% and 94%, respectively; the sensitivity for detecting ocular larval migrans was 64%. The combined performance of the new assay was superior to the currently available EIA and could potentially be employed to replace current assays that rely on native TES-Ag.

Development of a Luminex Bead Based Assay for Diagnosis of Toxocariasis Using Recombinant Antigens Tc-CTL-1 and Tc-TES-26

PubMed Central

Anderson, John P.; Rascoe, Lisa N.; Levert, Keith; Chastain, Holly M.; Reed, Matthew S.; Rivera, Hilda N.; McAuliffe, Isabel; Zhan, Bin; Wiegand, Ryan E.; Hotez, Peter J.; Wilkins, Patricia P.; Pohl, Jan; Handali, Sukwan

2015-01-01

The clinical spectrum of human disease caused by the roundworms Toxocara canis and Toxocara cati ranges from visceral and ocular larva migrans to covert toxocariasis. The parasite is not typically recovered in affected tissues, so detection of parasite-specific antibodies is usually necessary for establishing a diagnosis. The most reliable immunodiagnostic methods use the Toxocara excretory-secretory antigens (TES-Ag) in ELISA formats to detect Toxocara-specific antibodies. To eliminate the need for native parasite materials, we identified and purified immunodiagnostic antigens using 2D gel electrophoresis followed by electrospray ionization mass spectrometry. Three predominant immunoreactive proteins were found in the TES; all three had been previously described in the literature: Tc-CTL-1, Tc-TES-26, and Tc-MUC-3. We generated Escherichia coli expressed recombinant proteins for evaluation in Luminex based immunoassays. We were unable to produce a functional assay with the Tc-MUC-3 recombinant protein. Tc-CTL-1 and Tc-TES-26 were successfully coupled and tested using defined serum batteries. The use of both proteins together generated better results than if the proteins were used individually. The sensitivity and specificity of the assay for detecting visceral larval migrans using Tc-CTL-1 plus Tc-TES-26 was 99% and 94%, respectively; the sensitivity for detecting ocular larval migrans was 64%. The combined performance of the new assay was superior to the currently available EIA and could potentially be employed to replace current assays that rely on native TES-Ag. PMID:26485145

Clinical significance of TC21 overexpression in oral cancer.

PubMed

Macha, Muzafar A; Matta, Ajay; Sriram, Uma; Thakkar, Alok; Shukla, N K; Datta Gupta, Siddhartha; Ralhan, Ranju

2010-07-01

In search of novel molecular markers for oral cancer, we reported increased levels of TC21/R-Ras2 transcripts in oral squamous cell carcinoma by differential display. The aim of this study was to determine the clinical significance of TC21 in oral cancer. Immunohistochemical analysis of TC21 protein expression was carried out in 120 leukoplakias, 83 OSCCs and 30 non-malignant tissues, confirmed by immunoblotting, and correlated with clinicopathological parameters as well as disease prognosis. Co-immunoprecipitation assays were carried out to identify the interaction partners of TC21 protein in oral cancer cells and tissues. TC21 nuclear expression increased from normal oral tissues to leukoplakia and frank malignancy (P < 0.001). TC21 overexpression was observed in 74.2% leukoplakia with no dysplasia, 75.9% dysplasias and 79.5% OSCCs in comparison with normal oral tissues. Receiver operating characteristic analysis showed that the area-under-the curve values were 0.895, 0.885, and 0.919, while the positive predictive values were 95.8%, 95.6%, and 97.1%, for nuclear immunostaining for normal versus leukoplakia with no dysplasia, leukoplakic lesions with dysplasia, and OSCCs, respectively. Immunoblotting confirmed overexpression of TC21 in oral lesions. Using co-immunoprecipitation assays, we showed interactions of TC21 with Erk2, PI3-K, 14-3-3zeta and 14-3-3sigma proteins in oral cancer cells. Our findings suggested that alteration in TC21 expression is an early event in oral cancer and correlates with poor prognosis of OSCCs. TC21 interactions with Erk2, PI3-K, 14-3-3zeta and 14-3-3sigma proteins in oral cancer cells and tissues suggests the involvement of TC21 in signaling pathways in oral cancer.

Measuring hepatic functional reserve using T1 mapping of Gd-EOB-DTPA enhanced 3T MR imaging: A preliminary study comparing with 99mTc GSA scintigraphy and signal intensity based parameters.

PubMed

Nakagawa, Masataka; Namimoto, Tomohiro; Shimizu, Kie; Morita, Kosuke; Sakamoto, Fumi; Oda, Seitaro; Nakaura, Takeshi; Utsunomiya, Daisuke; Shiraishi, Shinya; Yamashita, Yasuyuki

2017-07-01

To determine the utility of liver T1-mapping on gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance (MR) imaging for the measurement of liver functional reserve compared with the signal intensity (SI) based parameters, technetium-99m-galactosyl serum albumin ( 99m Tc-GSA) scintigraphy and indocyanine green (ICG) clearance. This retrospective study included 111 patients (Child-Pugh-A 90; -B 21) performed with both Gd-EOB-DTPA enhanced liver MR imaging and 99m Tc-GSA (76 patients with ICG). Receiver operating characteristic (ROC) curve analysis was performed to compare diagnostic performances of T1-relaxation-time parameters [pre-(T1pre) and post-contrast (T1hb) Gd-EOB-DTPA], SI based parameters [relative enhancement (RE), liver-to-muscle-ratio (LMR), liver-to-spleen-ratio (LSR)] and 99m Tc-GSA scintigraphy blood clearance index (HH15)] for Child-Pugh classification. Pearson's correlation was used for comparisons among T1-relaxation-time parameters, SI-based parameters, HH15 and ICG. A significant difference was obtained for Child-Pugh classification with T1hb, ΔT1, all SI based parameters and HH15. T1hb had the highest AUC followed by RE, LMR, LSR, ΔT1, HH15 and T1pre. The correlation coefficients with HH15 were T1pre 0.22, T1hb 0.53, ΔT1 -0.38 of T1 relaxation parameters; RE -0.44, LMR -0.45, LSR -0.43 of SI-based parameters. T1hb was highest for correlation with HH15. The correlation coefficients with ICG were T1pre 0.29, T1hb 0.64, ΔT1 -0.42 of T1 relaxation parameters; RE -0.50, LMR -0.61, LSR -0.58 of SI-based parameters; 0.64 of HH15. Both T1hb and HH15 were highest for correlation with ICG. T1 relaxation time at post-contrast of Gd-EOB-DTPA (T1hb) was strongly correlated with ICG clearance and moderately correlated HH15 with 99m Tc-GSA. T1hb has the potential to provide robust parameter of liver functional reserve. Copyright © 2017 Elsevier B.V. All rights reserved.

Added value of non-calibrated and BMA calibrated AEMET-SREPS probabilistic forecasts: the 24 January 2009 extreme wind event over Catalonia

NASA Astrophysics Data System (ADS)

Escriba, P. A.; Callado, A.; Santos, D.; Santos, C.; Simarro, J.; García-Moya, J. A.

2009-09-01

At 00 UTC 24 January 2009 an explosive ciclogenesis originated over the Atlantic Ocean reached its maximum intensity with observed surface pressures lower than 970 hPa on its center and placed at Gulf of Vizcaya. During its path through southern France this low caused strong westerly and north-westerly winds over the Iberian Peninsula higher than 150 km/h at some places. These extreme winds leaved 10 casualties in Spain, 8 of them in Catalonia. The aim of this work is to show whether exists an added value in the short range prediction of the 24 January 2009 strong winds when using the Short Range Ensemble Prediction System (SREPS) of the Spanish Meteorological Agency (AEMET), with respect to the operational forecasting tools. This study emphasizes two aspects of probabilistic forecasting: the ability of a 3-day forecast of warn an extreme windy event and the ability of quantifying the predictability of the event so that giving value to deterministic forecast. Two type of probabilistic forecasts of wind are carried out, a non-calibrated and a calibrated one using Bayesian Model Averaging (BMA). AEMET runs daily experimentally SREPS twice a day (00 and 12 UTC). This system consists of 20 members that are constructed by integrating 5 local area models, COSMO (COSMO), HIRLAM (HIRLAM Consortium), HRM (DWD), MM5 (NOAA) and UM (UKMO), at 25 km of horizontal resolution. Each model uses 4 different initial and boundary conditions, the global models GFS (NCEP), GME (DWD), IFS (ECMWF) and UM. By this way it is obtained a probabilistic forecast that takes into account the initial, the contour and the model errors. BMA is a statistical tool for combining predictive probability functions from different sources. The BMA predictive probability density function (PDF) is a weighted average of PDFs centered on the individual bias-corrected forecasts. The weights are equal to posterior probabilities of the models generating the forecasts and reflect the skill of the ensemble members

Using Temperature Forecasts to Improve Seasonal Streamflow Forecasts in the Colorado and Rio Grande Basins

NASA Astrophysics Data System (ADS)

Lehner, F.; Wood, A.; Llewellyn, D.; Blatchford, D. B.; Goodbody, A. G.; Pappenberger, F.

2017-12-01

Recent studies have documented the influence of increasing temperature on streamflow across the American West, including snow-melt driven rivers such as the Colorado or Rio Grande. At the same time, some basins are reporting decreasing skill in seasonal streamflow forecasts, termed water supply forecasts (WSFs), over the recent decade. While the skill in seasonal precipitation forecasts from dynamical models remains low, their skill in predicting seasonal temperature variations could potentially be harvested for WSFs to account for non-stationarity in regional temperatures. Here, we investigate whether WSF skill can be improved by incorporating seasonal temperature forecasts from dynamical forecasting models (from the North American Multi Model Ensemble and the European Centre for Medium-Range Weather Forecast System 4) into traditional statistical forecast models. We find improved streamflow forecast skill relative to traditional WSF approaches in a majority of headwater locations in the Colorado and Rio Grande basins. Incorporation of temperature into WSFs thus provides a promising avenue to increase the robustness of current forecasting techniques in the face of continued regional warming.

Flash flood forecasting using simplified hydrological models, radar rainfall forecasts and data assimilation

NASA Astrophysics Data System (ADS)

Smith, P. J.; Beven, K.; Panziera, L.

2012-04-01

The issuing of timely flood alerts may be dependant upon the ability to predict future values of water level or discharge at locations where observations are available. Catchments at risk of flash flooding often have a rapid natural response time, typically less then the forecast lead time desired for issuing alerts. This work focuses on the provision of short-range (up to 6 hours lead time) predictions of discharge in small catchments based on utilising radar forecasts to drive a hydrological model. An example analysis based upon the Verzasca catchment (Ticino, Switzerland) is presented. Parsimonious time series models with a mechanistic interpretation (so called Data-Based Mechanistic model) have been shown to provide reliable accurate forecasts in many hydrological situations. In this study such a model is developed to predict the discharge at an observed location from observed precipitation data. The model is shown to capture the snow melt response at this site. Observed discharge data is assimilated to improve the forecasts, of up to two hours lead time, that can be generated from observed precipitation. To generate forecasts with greater lead time ensemble precipitation forecasts are utilised. In this study the Nowcasting ORographic precipitation in the Alps (NORA) product outlined in more detail elsewhere (Panziera et al. Q. J. R. Meteorol. Soc. 2011; DOI:10.1002/qj.878) is utilised. NORA precipitation forecasts are derived from historical analogues based on the radar field and upper atmospheric conditions. As such, they avoid the need to explicitly model the evolution of the rainfall field through for example Lagrangian diffusion. The uncertainty in the forecasts is represented by characterisation of the joint distribution of the observed discharge, the discharge forecast using the (in operational conditions unknown) future observed precipitation and that forecast utilising the NORA ensembles. Constructing the joint distribution in this way allows the full

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

Rainfall thresholds for forecasting landslides in the Seattle, Washington, area - exceedance and probability

USGS Publications Warehouse

Chleborad, Alan F.; Baum, Rex L.; Godt, Jonathan W.

2006-01-01

Empirical rainfall thresholds and related information form a basis for forecasting landslides in the Seattle area. A formula for a cumulative rainfall threshold (CT), P3=3.5-0.67P15, defined by rainfall amounts (in inches) during the last 3 days (72 hours), P3, and the previous 15 days (360 hours), P15, was developed from analysis of historical data for 91 landslides that occurred as part of 3-day events of three or more landslides between 1933 and 1997. Comparison with historical records for 577 landslides (including some used in developing the CT) indicates that the CT captures more than 90 percent of historical landslide events of three or more landslides in 1-day and 3-day periods that were recorded from 1978 to 2003. However, the probability of landslide occurrence on a day when the CT is exceeded at any single rain gage (8.4 percent) is low, and additional criteria are needed to confidently forecast landslide occurrence. Exceedance of a rainfall intensity-duration threshold I=3.257D-1.13, for intensity, I, (inch per hour) and duration, D, (hours), corresponds to a higher probability of landslide occurrence (42 percent at any 3 rain gages or 65 percent at any 10 rain gages), but it predicts fewer landslides. Both thresholds must be used in tandem to forecast landslide occurrence in Seattle.

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

DOE PAGES

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas; ...

2016-11-14

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

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

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast

PubMed Central

Moran, Kelly R.; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y.

2016-01-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. PMID:28830111

Space Weather Forecasting at IZMIRAN

NASA Astrophysics Data System (ADS)

Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

2017-12-01

Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

Interevent times in a new alarm-based earthquake forecasting model

NASA Astrophysics Data System (ADS)

Talbi, Abdelhak; Nanjo, Kazuyoshi; Zhuang, Jiancang; Satake, Kenji; Hamdache, Mohamed

2013-09-01

This study introduces a new earthquake forecasting model that uses the moment ratio (MR) of the first to second order moments of earthquake interevent times as a precursory alarm index to forecast large earthquake events. This MR model is based on the idea that the MR is associated with anomalous long-term changes in background seismicity prior to large earthquake events. In a given region, the MR statistic is defined as the inverse of the index of dispersion or Fano factor, with MR values (or scores) providing a biased estimate of the relative regional frequency of background events, here termed the background fraction. To test the forecasting performance of this proposed MR model, a composite Japan-wide earthquake catalogue for the years between 679 and 2012 was compiled using the Japan Meteorological Agency catalogue for the period between 1923 and 2012, and the Utsu historical seismicity records between 679 and 1922. MR values were estimated by sampling interevent times from events with magnitude M ≥ 6 using an earthquake random sampling (ERS) algorithm developed during previous research. Three retrospective tests of M ≥ 7 target earthquakes were undertaken to evaluate the long-, intermediate- and short-term performance of MR forecasting, using mainly Molchan diagrams and optimal spatial maps obtained by minimizing forecasting error defined by miss and alarm rate addition. This testing indicates that the MR forecasting technique performs well at long-, intermediate- and short-term. The MR maps produced during long-term testing indicate significant alarm levels before 15 of the 18 shallow earthquakes within the testing region during the past two decades, with an alarm region covering about 20 per cent (alarm rate) of the testing region. The number of shallow events missed by forecasting was reduced by about 60 per cent after using the MR method instead of the relative intensity (RI) forecasting method. At short term, our model succeeded in forecasting the

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

A positive feedback process between tropical cyclone intensity and the moisture conveyor belt assessed with Lagrangian diagnostics

NASA Astrophysics Data System (ADS)

Fujiwara, K.; Kawamura, R.; Hirata, H.; Kawano, T.

2017-12-01

Using a cloud-resolving regional model and Lagrangian diagnostics, we assess a positive feedback process between tropical cyclone (TC) intensity and the moisture conveyor belt (MCB), which connects a TC and the Indian Ocean (IO), the South China Sea (SCS), and the Philippine Sea vapors, from a macroscopic view. We performed sensitivity experiments that modified the observed sea surface temperature (SST) field over the IO and the SCS to regulate the MCB behavior, and we examined the remote response of a prototypical TC. The results show that the connection between MCB formation and TC development is very robust, which was also observed in another TC's case. The MCB plays a vital role in transporting lots of moist air parcels toward the TC from the remote ocean. The transported parcels are easily trapped in the inner core by radial inflow in the atmospheric boundary layer and, subsequently, release latent heat around the eye wall, resulting in the TC's intensifying. This acts to further penetrate the moist parcels of remote ocean origin into the inner core through the enhanced and expanded inflow. An additional experiment confirmed that the MCB is not formed unless the westward propagation of equatorial Rossby waves induced by TC heating overlaps with the background monsoon westerlies. These findings support the reliability and validity of TC-MCB feedback.

A Positive Feedback Process Between Tropical Cyclone Intensity and the Moisture Conveyor Belt Assessed With Lagrangian Diagnostics

NASA Astrophysics Data System (ADS)

Fujiwara, Keita; Kawamura, Ryuichi; Hirata, Hidetaka; Kawano, Tetsuya; Kato, Masaya; Shinoda, Taro

2017-12-01

Using a cloud-resolving regional model and Lagrangian diagnostics, we assess a positive feedback process between tropical cyclone (TC) intensity and the moisture conveyor belt (MCB), which connects a TC and the Indian Ocean (IO), the South China Sea (SCS), and the Philippine Sea (PS) vapors, from a macroscopic view. We performed sensitivity experiments that modified the observed sea surface temperature field over the IO and the SCS to regulate the MCB behavior, and we examined the remote response of a prototypical TC. The results show that the connection between MCB formation and TC development is very robust, which was also observed in another TC's case. The MCB plays a vital role in transporting lots of moist air parcels toward the TC from the IO, SCS, and PS regions. The transported parcels, which further gained the underlying ocean vapor along the MCB, are easily trapped in the inner core by radial inflow in the atmospheric boundary layer and, subsequently, release latent heat around the eyewall, resulting in the TC's intensifying. This acts to further penetrate the moist parcels of remote ocean origin into the inner core through the enhanced and expanded inflow. An additional experiment suggested that the MCB is not formed unless the westward propagation of equatorial waves induced by TC heating overlaps with the background monsoon westerlies. These findings support the reliability and validity of TC-MCB feedback.

Revised forecast: Another stormy summer ahead

NASA Astrophysics Data System (ADS)

Carlowicz, Michael

After predicting in November 1995 that the 1996 hurricane season would be less active than the typical year (Eos, December 12, 1995), William Gray and his colleagues from Colorado State University have revised their forecast. Plugging updated atmospheric data into their statistical model, the researchers are now predicting seven hurricanes—two of them intense (category 3, 4, or 5)—and 11 named storms for the summer and fall of 1996. Net tropical cyclone activity for the hurricane season, which lasts from June 1 to December 1, should be 105% of the 25-year average, according to Gray.In November, Gray and Chris Landsea of NOAA's Hurricane Research Division predicted eight tropical storms and five hurricanes (two intense), less than the historical averages of 9.3 named storms and 5.7 hurricanes per season. The change in expectations is the result of new accounting for trends in temperature and barometric pressure in Africa and around the Atlantic Basin.

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

Bayesian analyses of seasonal runoff forecasts

NASA Astrophysics Data System (ADS)

Krzysztofowicz, R.; Reese, S.

1991-12-01

Forecasts of seasonal snowmelt runoff volume provide indispensable information for rational decision making by water project operators, irrigation district managers, and farmers in the western United States. Bayesian statistical models and communication frames have been researched in order to enhance the forecast information disseminated to the users, and to characterize forecast skill from the decision maker's point of view. Four products are presented: (i) a Bayesian Processor of Forecasts, which provides a statistical filter for calibrating the forecasts, and a procedure for estimating the posterior probability distribution of the seasonal runoff; (ii) the Bayesian Correlation Score, a new measure of forecast skill, which is related monotonically to the ex ante economic value of forecasts for decision making; (iii) a statistical predictor of monthly cumulative runoffs within the snowmelt season, conditional on the total seasonal runoff forecast; and (iv) a framing of the forecast message that conveys the uncertainty associated with the forecast estimates to the users. All analyses are illustrated with numerical examples of forecasts for six gauging stations from the period 1971 1988.

Radar-driven high-resolution hydro-meteorological forecasts of the 26 September 2007 Venice flash flood

NASA Astrophysics Data System (ADS)

Rossa, Andrea M.; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

2010-11-01

SummaryThis study aims to assess the feasibility of assimilating carefully checked radar rainfall estimates into a numerical weather prediction (NWP) to extend the forecasting lead time for an extreme flash flood. The hydro-meteorological modeling chain includes the convection-permitting NWP model COSMO-2 and a coupled hydrological-hydraulic model. Radar rainfall estimates are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood which impacted the coastal area of North-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the 90 km2 Dese river basin draining to the Venice Lagoon. The radar rainfall observations are carefully checked for artifacts, including rain-induced signal attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar rainfall estimates in the assimilation cycle of the NWP model is very significant. The main individual organized convective systems are successfully introduced into the model state, both in terms of timing and localization. Also, high-intensity incorrectly localized precipitation is correctly reduced to about the observed levels. On the other hand, the highest rainfall intensities computed after assimilation underestimate the observed values by 20% and 50% at a scale of 20 km and 5 km, respectively. The positive impact of assimilating radar rainfall estimates is carried over into the free forecast for about 2-5 h, depending on when the forecast was started. The positive impact is larger when the main mesoscale convective system is present in the initial conditions. The improvements in the precipitation forecasts are propagated to the river flow simulations, with an extension of the forecasting lead time up to 3 h.

Infection with Trypanosoma cruzi TcII and TcI in free-ranging population of lion tamarins (Leontopithecus spp): an 11-year follow-up.

PubMed

Lisboa, Cristiane Varella; Monteiro, Rafael Veríssimo; Martins, Andreia Fonseca; Xavier, Samantha Cristina das Chagas; Lima, Valdirene Dos Santos; Jansen, Ana Maria

2015-05-01

Here, we present a review of the dataset resulting from the 11-years follow-up of Trypanosoma cruzi infection in free-ranging populations of Leontopithecus rosalia (golden lion tamarin) and Leontopithecus chrysomelas (golden-headed lion tamarin) from distinct forest fragments in Atlantic Coastal Rainforest. Additionally, we present new data regarding T. cruzi infection of small mammals (rodents and marsupials) that live in the same areas as golden lion tamarins and characterisation at discrete typing unit (DTU) level of 77 of these isolates. DTU TcII was found to exclusively infect primates, while TcI infected Didelphis aurita and lion tamarins. The majority of T. cruzi isolates derived from L. rosalia were shown to be TcII (33 out 42) Nine T. cruzi isolates displayed a TcI profile. Golden-headed lion tamarins demonstrated to be excellent reservoirs of TcII, as 24 of 26 T. cruzi isolates exhibited the TcII profile. We concluded the following: (i) the transmission cycle of T. cruzi in a same host species and forest fragment is modified over time, (ii) the infectivity competence of the golden lion tamarin population fluctuates in waves that peak every other year and (iii) both golden and golden-headed lion tamarins are able to maintain long-lasting infections by TcII and TcI.

Evaluation of a wildfire smoke forecasting system as a tool for public health protection.

PubMed

Yao, Jiayun; Brauer, Michael; Henderson, Sarah B

2013-10-01

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. 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. 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. 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. 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.

Effect of Sulfate Aerosol Geoengineering on Tropical cyclones

NASA Astrophysics Data System (ADS)

Wang, Q.; Moore, J.; Ji, D.

2017-12-01

Variation in tropical cyclone (TC) number and intensity is driven in part by changes in the thermodynamics that can be defined by ocean and atmospheric variables. Genesis Potential Index (GPI) and ventilation index (VI) are combinations of potential intensity, vertical wind shear, relative humidity, midlevel entropy deficit, and absolute vorticity that quantify thermodynamic forcing of TC activity under changed climates, and can be calculated from climate model output. Here we use five CMIP5 models running the RCP45 experiment the Geoengineering Model Intercomparison Project (GeoMIP) stratospheric aerosol injection G4 experiment to calculate the two indices over the 2020 to 2069 period. Globally, GPI under G4 is lower than under RCP45, though both have a slight increasing trend. Spatial patterns in the relative effectiveness of geoengineering show reductions in TC in all models in the North Atlantic basin, and northern Indian Ocean in all except NorESM1-M. In the North Pacific, most models also show relative reductions under G4. VI generally coincide with the GPI patterns. Most models project Potential intensity and Relative Humidity to be the dominant variable to affect genesis potential. Changes in vertical wind shear and vorticity are small with scatter across different models and ocean basins. We find that tropopause temperature maybe as important as sea surface temperature in effecting TC genesis. Thus stratospheric aerosol geoengineering impacts on potential intensity and hence TC intensity are reasonably consistent, but probably underestimated by statistical forecasts of Tropical North Atlantic hurricane activity driven by sea surface temperatures alone. However the impacts of geoengineering on other ocean basins are more difficult to assess, and require more complete understanding of their driving parameters under present day climates. Furthermore, the possible effects of stratospheric injection on chemical reactions in the stratosphere, such as ozone, are

From Tornadoes to Earthquakes: Forecast Verification for Binary Events Applied to the 1999 Chi-Chi, Taiwan, Earthquake

NASA Astrophysics Data System (ADS)

Chen, C.; Rundle, J. B.; Holliday, J. R.; Nanjo, K.; Turcotte, D. L.; Li, S.; Tiampo, K. F.

2005-12-01

Forecast verification procedures for statistical events with binary outcomes typically rely on the use of contingency tables and Relative Operating Characteristic (ROC) diagrams. Originally developed for the statistical evaluation of tornado forecasts on a county-by-county basis, these methods can be adapted to the evaluation of competing earthquake forecasts. Here we apply these methods retrospectively to two forecasts for the m = 7.3 1999 Chi-Chi, Taiwan, earthquake. These forecasts are based on a method, Pattern Informatics (PI), that locates likely sites for future large earthquakes based on large change in activity of the smallest earthquakes. A competing null hypothesis, Relative Intensity (RI), is based on the idea that future large earthquake locations are correlated with sites having the greatest frequency of small earthquakes. We show that for Taiwan, the PI forecast method is superior to the RI forecast null hypothesis. Inspection of the two maps indicates that their forecast locations are indeed quite different. Our results confirm an earlier result suggesting that the earthquake preparation process for events such as the Chi-Chi earthquake involves anomalous changes in activation or quiescence, and that signatures of these processes can be detected in precursory seismicity data. Furthermore, we find that our methods can accurately forecast the locations of aftershocks from precursory seismicity changes alone, implying that the main shock together with its aftershocks represent a single manifestation of the formation of a high-stress region nucleating prior to the main shock.

Predictability and prediction of tropical cyclones on daily to interannual time scales

NASA Astrophysics Data System (ADS)

Belanger, James Ian

The spatial and temporal complexity of tropical cyclones (TCs) raises a number of scientific questions regarding their genesis, movement, intensification, and variability. In this dissertation, the principal goal is to determine the current state of predictability for each of these processes using global numerical prediction systems. The predictability findings are then used in conjunction with several new statistical calibration techniques to develop a proof-of-concept, operational forecast system for North Atlantic TCs on daily to intraseasonal time scales. To quantify the current extent of tropical cyclone predictability, we assess probabilistic forecasts from the most advanced global numerical weather prediction system to date, the ECMWF Variable Resolution Ensemble Prediction System (VarEPS; Hamill et al. 2008, Hagedorn et al. 2012). Using a new false alarm clustering technique to maximize the utility of the VarEPS, the ensemble system is shown to provide well-calibrated probabilistic forecasts for TC genesis through a lead-time of one week and pregenesis track forecasts with similar skill compared to the VarEPS's postgenesis track forecasts. These findings provide evidence that skillful real-time TC genesis predictions may be made in the North Indian Ocean—a region that even today has limited forecast warning windows for TCs relative to other ocean basins. To quantify the predictability of TCs on intraseasonal time scales, forecasts from the ECMWF Monthly Forecast System (ECMFS) are examined for the North Atlantic Ocean. From this assessment, dynamically based forecasts from the ECMFS provide forecast skill exceeding climatology out to weeks three and four for portions of the southern Gulf of Mexico, western Caribbean and the Main Development Region. Forecast skill in these regions is traced to the model's ability to capture correctly the variability in deep-layer vertical wind shear as well as the relative frequency of easterly waves moving through these

Data Assimilation of AIRS Water Vapor Profiles: Impact on Precipitation Forecasts for Atmospheric River Cases Affecting the Western of the United States

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Jedlovec, Gary; Wick, Gary; Neiman, Paul

2013-01-01

Atmospheric rivers are transient, narrow regions in the atmosphere responsible for the transport of large amounts of water vapor. These phenomena can have a large impact on precipitation. In particular, they can be responsible for intense rain events on the western coast of North America during the winter season. This paper focuses on attempts to improve forecasts of heavy precipitation events in the Western US due to atmospheric rivers. Profiles of water vapor derived from from Atmospheric Infrared Sounder (AIRS) observations are combined with GFS forecasts by a three-dimensional variational data assimilation in the Gridpoint Statistical Interpolation (GSI). Weather Research and Forecasting (WRF) forecasts initialized from the combined field are compared to forecasts initialized from the GFS forecast only for 3 test cases in the winter of 2011. Results will be presented showing the impact of the AIRS profile data on water vapor and temperature fields, and on the resultant precipitation forecasts.

IEA Wind Task 36 Forecasting

NASA Astrophysics Data System (ADS)

Giebel, Gregor; Cline, Joel; Frank, Helmut; Shaw, Will; Pinson, Pierre; Hodge, Bri-Mathias; Kariniotakis, Georges; Sempreviva, Anna Maria; Draxl, Caroline

2017-04-01

Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Wind Power Forecasting tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, …) and operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets for verification. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts aiming at industry and forecasters alike. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions, especially probabilistic ones. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Joel Cline of the US Department of Energy. Collaboration in the task is solicited from everyone interested in the forecasting business. We will collaborate with IEA Task 31 Wakebench, which developed the Windbench benchmarking platform, which this task will use for forecasting benchmarks. The task runs for three years, 2016-2018. Main deliverables are an up-to-date list of current projects and main project results, including datasets which can be used by researchers around the world to improve their own models, an IEA Recommended Practice on performance evaluation of probabilistic forecasts, a position paper regarding the use of probabilistic forecasts

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

[99mTc(V)-DMSA accumulation in gynecomastia].

PubMed

Ohta, H

1998-11-01

The accumulation of 99mTc(V)-DMSA in bilateral breasts was recognized in a 60-year-old male with drug-induced gynecomastia. There are some reports describing 99mTc(V)-DMSA accumulation in normal female breast, fibrous dysplasia of the breast and metastatic lesions of breast carcinoma, but to my knowledge, there have been no reports describing 99mTc(V)-DMSA accumulation in gynecomastia.

Tc17 cells in patients with uterine cervical cancer.

PubMed

Zhang, Yan; Hou, Fei; Liu, Xin; Ma, Daoxin; Zhang, Youzhong; Kong, Beihua; Cui, Baoxia

2014-01-01

The existence of Tc17 cells was recently shown in several types of infectious and autoimmune diseases, but their distribution and functions in uterine cervical cancer (UCC) have not been fully elucidated. The frequency of Tc17 cells in peripheral blood samples obtained from UCC patients, cervical intraepithelial neoplasia (CIN) patients and healthy controls was determined by flow cytometry. Besides, the prevalence of Tc17 cells and their relationships to Th17 cells and Foxp3-expressing T cells as well as microvessels in tissue samples of the patients were assessed by immunohistochemistry staining. Compared to controls, patients with UCC or CIN had a higher proportion of Tc17 cells in both peripheral blood and cervical tissues, but the level of Tc17 cells in UCC tissues was significantly higher than that in CIN tissues. Besides, the increased level of Tc17 in UCC patients was associated with the status of pelvic lymph node metastases and increased microvessel density. Finally, significant correlations of infiltration between Tc17 cells and Th17 cells or Foxp3-expressing T cells were observed in UCC and CIN tissues. This study indicates that Tc17 cell infiltration in cervical cancers is associated with cancer progression accompanied by increased infiltrations of Th17 cells and regulatory T cells as well as promoted tumor vasculogenesis.

Tc17 Cells in Patients with Uterine Cervical Cancer

PubMed Central

Zhang, Yan; Hou, Fei; Liu, Xin; Ma, Daoxin; Zhang, Youzhong; Kong, Beihua; Cui, Baoxia

2014-01-01

Background The existence of Tc17 cells was recently shown in several types of infectious and autoimmune diseases, but their distribution and functions in uterine cervical cancer (UCC) have not been fully elucidated. Methods The frequency of Tc17 cells in peripheral blood samples obtained from UCC patients, cervical intraepithelial neoplasia (CIN) patients and healthy controls was determined by flow cytometry. Besides, the prevalence of Tc17 cells and their relationships to Th17 cells and Foxp3-expressing T cells as well as microvessels in tissue samples of the patients were assessed by immunohistochemistry staining. Results Compared to controls, patients with UCC or CIN had a higher proportion of Tc17 cells in both peripheral blood and cervical tissues, but the level of Tc17 cells in UCC tissues was significantly higher than that in CIN tissues. Besides, the increased level of Tc17 in UCC patients was associated with the status of pelvic lymph node metastases and increased microvessel density. Finally, significant correlations of infiltration between Tc17 cells and Th17 cells or Foxp3-expressing T cells were observed in UCC and CIN tissues. Conclusions This study indicates that Tc17 cell infiltration in cervical cancers is associated with cancer progression accompanied by increased infiltrations of Th17 cells and regulatory T cells as well as promoted tumor vasculogenesis. PMID:24523865

Synthesis, Characterization, and Initial Biological Evaluation of [99m Tc]Tc-Tricarbonyl-labeled DPA-α-MSH Peptide Derivatives for Potential Melanoma Imaging.

PubMed

Gao, Feng; Sihver, Wiebke; Bergmann, Ralf; Belter, Birgit; Bolzati, Cristina; Salvarese, Nicola; Steinbach, Jörg; Pietzsch, Jens; Pietzsch, Hans-Jürgen

2018-06-06

α-Melanocyte stimulating hormone (α-MSH) derivatives target the melanocortin-1 receptor (MC1R) specifically and selectively. In this study, the α-MSH-derived peptide NAP-NS1 (Nle-Asp-His-d-Phe-Arg-Trp-Gly-NH 2 ) with and without linkers was conjugated with 5-(bis(pyridin-2-ylmethyl)amino)pentanoic acid (DPA-COOH) and labeled with [ 99m Tc]Tc-tricarbonyl by two methods. With the one-pot method the labeling was faster than with the two-pot method, while obtaining similarly high yields. Negligible trans-chelation and high stability in physiological solutions was determined for the [ 99m Tc]Tc-tricarbonyl-peptide conjugates. Coupling an ethylene glycol (EG)-based linker increased the hydrophilicity. The peptide derivatives displayed high binding affinity in murine B16F10 melanoma cells as well as in human MeWo and TXM13 melanoma cell homogenates. Preliminary in vivo studies with one of the [ 99m Tc]Tc-tricarbonyl-peptide conjugates showed good stability in blood and both renal and hepatobiliary excretion. Biodistribution was performed on healthy rats to gain initial insight into the potential relevance of the 99m Tc-labeled peptides for in vivo imaging. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hydrological Forecasting Practices in Brazil

NASA Astrophysics Data System (ADS)

Fan, Fernando; Paiva, Rodrigo; Collischonn, Walter; Ramos, Maria-Helena

2016-04-01

This work brings a review on current hydrological and flood forecasting practices in Brazil, including the main forecasts applications, the different kinds of techniques that are currently being employed and the institutions involved on forecasts generation. A brief overview of Brazil is provided, including aspects related to its geography, climate, hydrology and flood hazards. A general discussion about the Brazilian practices on hydrological short and medium range forecasting is presented. Detailed examples of some hydrological forecasting systems that are operational or in a research/pre-operational phase using the large scale hydrological model MGB-IPH are also presented. Finally, some suggestions are given about how the forecasting practices in Brazil can be understood nowadays, and what are the perspectives for the future.

Re-Search for Extinct 99Tc and 98Tc in the Early Solar System

NASA Astrophysics Data System (ADS)

Yin, Q.; Jagoutz, E.; Wanke, H.

1992-07-01

The recent advances in negative thermal ionization mass spectrometry (N-TIMS) of Re and Os (Creaser et al., 1991) offer a new chance to search for isotopic anomalies of ruthenium (Ru) (and possibly Mo) in meteorites. The Ru isotopes are particularly important since they contain two daughter decay products of technicium, ^98Tc (tau(sub)1/2=4.2x10^6 yr) and ^99Tc (tau(sub)1/2=2.1x10^5 yr). Natural Tc is now extinct on Earth due to their short half-life, but may have been present in the early solar system; Ru isotopes might also bear witness of the various processes of nucleosynthesis and of the imperfect mixing of their products in the pre-solar nebula; Ru isotopic composition in fission is drastically different from natural; ^99Tc is crucial because of its very short half-life and is observed directly for several half-lives in s-process-enriched stars during the thermally pulsing, AGB (asymptotic giant branch) phase of evolution. The probability of detecting ^99Tc in this type of stars is typically 70% (Smith and Lambert, 1988). The chemical similarities between Ru and Os yield correspondingly high ionization efficiency for Ru with N-TIMS. Ru is obtained as a byproduct of Os chemistry, as Ru co-distills with Os. This unique combination conveniently enables a survey for extinct Tc by determining isotopic composition of Ru on a wide range of samples together with extensive studies of Re-Os system in geochemical community in the years to come. These arguments prompted us to carry out a systematic re-search for Ru isotopic anomalies initiated by Herr and coworkers more than 30 years ago (Herr et al., 1958). We have measured Ru isotopic composition in one bulk sample and a magnetic fraction of Maralinga carbonaceous chondrite and one bulk sample of the iron meteorite Gibeon. The bulk sample of Maralinga is found to be isotopically indistinguishable from the terrestrial values within analytical uncertainties. In the magnetic fraction, however, a positive deviation (0

Tc-99m Ethylenedicysteine and Tc-99m Dimercaptosuccinic Acid Scintigraphy-Comparison of the Two for Detection of Scarring and Differential Cortical Function.

PubMed

Dharmalingam, Anitha; Pawar, Shwetal U; Parelkar, Sandesh V; Shetye, Suruchi S; Ghorpade, Mangala K; Tilve, Gundu H

2017-01-01

The differential cortical function obtained by Tc-99m EC is comparable to that of Tc-99m DMSA. However, identification of scars on Tc-99m EC images needs to be studied. The aim of the study is to evaluate role of Tc-99m EC for detection of scarring and differential cortical function by comparing with Tc-99m DMSA. Prospective observational study of recurrent UTI; minimum 6 weeks after acute episode; when urine examination is negative for pus cells. Forty-seven children with normal positioned kidneys underwent Tc-99m EC and DMSA scintigraphy. The DRF and cortical phase images of both studies in the same image matrix size were evaluated by two independent observers for scarring; Tc-99m DMSA was considered as the gold standard. MS Excel 2007 and GraphPad Instat V3.1 and ROC analysis. There was no significant difference in the detection of scarring using two studies with Cohen's kappa coefficient (κ) 0.932. The sensitivity and specificity of Tc-99m EC for detection of scarring was 98.75% and 99.15%, respectively. There was good agreement between the differential cortical function calculated using two studies. The summed Tc-99m EC images with an acceptable high image contrast allow detection of cortical scarring in patients with normal kidney positions. It is an excellent single-modality comprehensive investigational agent for renal parenchymal defects, function, and excretion evaluation with the added advantages of lower cost, convenience, and low radiation exposure to the child.

Weather assessment and forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

Inhibitory effect of trans-caryophyllene (TC) on leukocyte-endothelial attachment.

PubMed

Zhang, Zhen; Yang, Chunfeng; Dai, Xinlun; Ao, Yu; Li, Yumei

2017-08-15

trans-Caryophyllene (TC) is a major component found in the essential oils of many spices and foods/medicinal plants. It is a natural sesquiterpene and has been the subject of numerous studies. However, the effects of TC on vascular inflammation remain unknown. In this study, we reported that TC treatment in human umbilical vein endothelial cells (HUVECs) prevented attachment of monocytic leukemia cell line THP-1 cells to endothelial cells. In addition, in vivo results indicate that TC inhibited macrophage infiltration to the aortic surface and reduced total serum levels of cholesterol and triglycerides. Importantly, administration of TC could inhibit the induction of vascular cell adhesion molecule-1 (VCAM-1) both in vitro and in vivo. Notably, our data indicate that the inhibitory effects of TC on the expression of VCAM-1 are mediated by the JAK2/STAT1/IRF-1 pathway. TC is a specific agonist of the type 2 cannabinoid receptor (CB2R). Importantly, we further verified that the inhibitory effects of TC on the expression of IRF-1 and VCAM-1 are dependent on activation of CB2R. Inhibition of CB2R by either specific inhibitors or RNA interference abolished the inhibitory effects of TC on the expression of IRF-1 and VCAM-1. Our results suggest that TC might have a capacity to suppress the development of atherosclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Testing an innovative framework for flood forecasting, monitoring and mapping in Europe

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Kalas, Milan; Lorini, Valerio; Wania, Annett; Pappenberger, Florian; Salamon, Peter; Ramos, Maria Helena; Cloke, Hannah; Castillo, Carlos

2017-04-01

Between May and June 2016, France was hit by severe floods, particularly in the Loire and Seine river basins. In this work, we use this case study to test an innovative framework for flood forecasting, mapping and monitoring. More in detail, the system integrates in real-time two components of the Copernicus Emergency mapping services, namely the European Flood Awareness System and the satellite-based Rapid Mapping, with new procedures for rapid risk assessment and social media and news monitoring. We explore in detail the performance of each component of the system, demonstrating the improvements in respect to stand-alone flood forecasting and monitoring systems. We show how the performances of the forecasting component can be refined using the real-time feedback from social media monitoring to identify which areas were flooded, to evaluate the flood intensity, and therefore to correct impact estimations. Moreover, we show how the integration with impact forecast and social media monitoring can improve the timeliness and efficiency of satellite based emergency mapping, and reduce the chances of missing areas where flooding is already happening. These results illustrate how the new integrated approach leads to a better and earlier decision making and a timely evaluation of impacts.

Infection with Trypanosoma cruzi TcII and TcI in free-ranging population of lion tamarins (Leontopithecus spp): an 11-year follow-up

PubMed Central

Lisboa, Cristiane Varella; Monteiro, Rafael Veríssimo; Martins, Andreia Fonseca; Xavier, Samantha Cristina das Chagas; Lima, Valdirene dos Santos; Jansen, Ana Maria

2015-01-01

Here, we present a review of the dataset resulting from the 11-years follow-up of Trypanosoma cruzi infection in free-ranging populations of Leontopithecus rosalia (golden lion tamarin) and Leontopithecus chrysomelas (golden-headed lion tamarin) from distinct forest fragments in Atlantic Coastal Rainforest. Additionally, we present new data regarding T. cruzi infection of small mammals (rodents and marsupials) that live in the same areas as golden lion tamarins and characterisation at discrete typing unit (DTU) level of 77 of these isolates. DTU TcII was found to exclusively infect primates, while TcI infected Didelphis aurita and lion tamarins. The majority of T. cruzi isolates derived from L. rosalia were shown to be TcII (33 out 42) Nine T. cruzi isolates displayed a TcI profile. Golden-headed lion tamarins demonstrated to be excellent reservoirs of TcII, as 24 of 26 T. cruzi isolates exhibited the TcII profile. We concluded the following: (i) the transmission cycle of T. cruzi in a same host species and forest fragment is modified over time, (ii) the infectivity competence of the golden lion tamarin population fluctuates in waves that peak every other year and (iii) both golden and golden-headed lion tamarins are able to maintain long-lasting infections by TcII and TcI. PMID:25946156

A VVWBO-BVO-based GM (1,1) and its parameter optimization by GRA-IGSA integration algorithm for annual power load forecasting

PubMed Central

Wang, Hongguang

2018-01-01

Annual power load forecasting is not only the premise of formulating reasonable macro power planning, but also an important guarantee for the safety and economic operation of power system. In view of the characteristics of annual power load forecasting, the grey model of GM (1,1) are widely applied. Introducing buffer operator into GM (1,1) to pre-process the historical annual power load data is an approach to improve the forecasting accuracy. To solve the problem of nonadjustable action intensity of traditional weakening buffer operator, variable-weight weakening buffer operator (VWWBO) and background value optimization (BVO) are used to dynamically pre-process the historical annual power load data and a VWWBO-BVO-based GM (1,1) is proposed. To find the optimal value of variable-weight buffer coefficient and background value weight generating coefficient of the proposed model, grey relational analysis (GRA) and improved gravitational search algorithm (IGSA) are integrated and a GRA-IGSA integration algorithm is constructed aiming to maximize the grey relativity between simulating value sequence and actual value sequence. By the adjustable action intensity of buffer operator, the proposed model optimized by GRA-IGSA integration algorithm can obtain a better forecasting accuracy which is demonstrated by the case studies and can provide an optimized solution for annual power load forecasting. PMID:29768450

Effective visualization of suppressed thyroid tissue by means of baseline 99mTc-methoxy isobutyl isonitrile in comparison with 99mTc-pertechnetate scintigraphy after TSH stimulation.

PubMed

Vattimo, A; Bertelli, P; Burroni, L

1992-01-01

Baseline 99mTc-MIBI thyroid scintigraphy was compared with 99mTc-pertechnetate scintigraphy after TSH stimulation in seven patients with suppressed thyroid tissue due to an autonomously functioning thyroid nodule (AFTN). In all patients the suppressed thyroid tissue was visualized by means of both baseline 99mTc-MIBI and post-TSH 99mTc-pertechnetate scintigraphy, and in some cases the former technique provided better visualization. In one patient presenting a "warm" nodule T3-suppression did not affect the nodular/extranodular uptake ratio of 99mTc-MIBI, whereas the 99mTc-pertechnetate uptake ratio increased significantly. This leads us to hypothesize that the thyroid uptake of 99mTc-MIBI is not related to TSH control, but rather to other mechanisms such as the blood flow. Since exogenous TSH is no longer available, 99mTc-MIBI scintigraphy can be successfully used in the place of repeated 99mTc-pertechnetate scintigraphy after TSH stimulation in the assessment of AFTN.

Sub-Seasonal Climate Forecast Rodeo

NASA Astrophysics Data System (ADS)

Webb, R. S.; Nowak, K.; Cifelli, R.; Brekke, L. D.

2017-12-01

The Bureau of Reclamation, as the largest water wholesaler and the second largest producer of hydropower in the United States, benefits from skillful forecasts of future water availability. Researchers, water managers from local, regional, and federal agencies, and groups such as the Western States Water Council agree that improved precipitation and temperature forecast information at the sub-seasonal to seasonal (S2S) timescale is an area with significant potential benefit to water management. In response, and recognizing NOAA's leadership in forecasting, Reclamation has partnered with NOAA to develop and implement a real-time S2S forecasting competition. For a year, solvers are submitting forecasts of temperature and precipitation for weeks 3&4 and 5&6 every two weeks on a 1x1 degree grid for the 17 western state domain where Reclamation operates. The competition began on April 18, 2017 and the final real-time forecast is due April 3, 2018. Forecasts are evaluated once observational data become available using spatial anomaly correlation. Scores are posted on a competition leaderboard hosted by the National Integrated Drought Information System (NIDIS). The leaderboard can be accessed at: https://www.drought.gov/drought/sub-seasonal-climate-forecast-rodeo. To be eligible for cash prizes - which total $800,000 - solvers must outperform two benchmark forecasts during the real-time competition as well as in a required 11-year hind-cast. To receive a prize, competitors must grant a non-exclusive license to practice their forecast technique and make it available as open source software. At approximately one quarter complete, there are teams outperforming the benchmarks in three of the four competition categories. With prestige and monetary incentives on the line, it is hoped that the competition will spur innovation of improved S2S forecasts through novel approaches, enhancements to established models, or otherwise. Additionally, the competition aims to raise

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel; Kyriakidis, P.; Verdin, James P.; Funk, Chris; Galu, Gideon

2011-01-01

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

MMAB Sea Ice Forecast Page

Science.gov Websites

verification statistics Grumbine, R. W., Virtual Floe Ice Drift Forecast Model Intercomparison, Weather and Forecasting, 13, 886-890, 1998. MMAB Note: Virtual Floe Ice Drift Forecast Model Intercomparison 1996 pdf ~47

Prediction of Winter Storm Tracks and Intensities Using the GFDL fvGFS Model

NASA Astrophysics Data System (ADS)

Rees, S.; Boaggio, K.; Marchok, T.; Morin, M.; Lin, S. J.

2017-12-01

The GFDL Finite-Volume Cubed-Sphere Dynamical core (FV3) is coupled to a modified version of the Global Forecast System (GFS) physics and initial conditions, to form the fvGFS model. This model is similar to the one being implemented as the next-generation operational weather model for the NWS, which is also FV3-powered. Much work has been done to verify fvGFS tropical cyclone prediction, but little has been done to verify winter storm prediction. These costly and dangerous storms impact parts of the U.S. every year. To verify winter storms we ran the NCEP operational cyclone tracker, developed at GFDL, on semi-real-time 13 km horizontal resolution fvGFS forecasts. We have found that fvGFS compares well to the operational GFS in storm track and intensity, though often predicts slightly higher intensities. This presentation will show the track and intensity verification from the past two winter seasons and explore possible reasons for bias.

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast.

PubMed

Moran, Kelly R; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y

2016-12-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The Impact of Microphysical Schemes on Hurricane Intensity and Track

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shi, Jainn Jong; Chen, Shuyi S.; Lang, Stephen; Lin, Pay-Liam; Hong, Song-You; Peters-Lidard, Christa; Hou, Arthur

2011-01-01

During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated

Real-time Monitoring of 2017 Hurricanes and Typhoons with Lightning

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Thomas, J. N.; Bracy, C.; Holzworth, R. H., II

2017-12-01

The 2017 Atlantic season had the highest number of major hurricanes since 2005. To tackle the demand of real-time tropical cyclone (TC) monitoring, our group has developed a unique "storm-following" satellite and ground-based lightning product known as WWLLN-TC (World Wide Lightning Location Network - Tropical Cyclones; http://wwlln.net/storms/). In the present study, we explore this tool and other datasets, combining lightning and microwave data to quantify areas of intense convection in 2017 TCs Harvey, Hato, Irma, Maria, Nate, Ophelia and others. For each storm, the temporal distribution of discharges outside and within the inner core is compared to the changes in TC intensity. The intensification processes, monitored in near real-time by WWLLN-TC, are quantified in terms of pressure and/or wind speed changes. A peak in lightning activity is often observed in the inner core of TCs before and during rapid weakening, such as in Hurricanes Irma and Maria and Typhoon Hato. The microwave frequencies investigated include the 37 to 183 GHz channels of the satellite sensors DMSP/SSMIS and GPM/GMI. We reconstruct brightness temperatures from lightning data, providing more detailed pictures of the evolution of TCs at moments when satellite passes are missing or incomplete. This study also compares lightning activity in the inner core with convective and environmental parameters. Examples of environmental parameters discussed are sea surface temperature, wind shear, and sea surface height anomalies. We conclude by considering possible implications of WWLLN-TC on forecasts of rapid intensity change and rainfall.

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

Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

NASA Astrophysics Data System (ADS)

Fabianová, Jana; Kačmáry, Peter; Molnár, Vieroslav; Michalik, Peter

2016-10-01

Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

Accuracy of forecasts in strategic intelligence

PubMed Central

Mandel, David R.; Barnes, Alan

2014-01-01

The accuracy of 1,514 strategic intelligence forecasts abstracted from intelligence reports was assessed. The results show that both discrimination and calibration of forecasts was very good. Discrimination was better for senior (versus junior) analysts and for easier (versus harder) forecasts. Miscalibration was mainly due to underconfidence such that analysts assigned more uncertainty than needed given their high level of discrimination. Underconfidence was more pronounced for harder (versus easier) forecasts and for forecasts deemed more (versus less) important for policy decision making. Despite the observed underconfidence, there was a paucity of forecasts in the least informative 0.4–0.6 probability range. Recalibrating the forecasts substantially reduced underconfidence. The findings offer cause for tempered optimism about the accuracy of strategic intelligence forecasts and indicate that intelligence producers aim to promote informativeness while avoiding overstatement. PMID:25024176

Getters for Tc and I Removal from Liquid Waste

NASA Astrophysics Data System (ADS)

Qafoku, N. P.; Asmussen, M.; Lawter, A.; Neeway, J.; Smith, G.

2015-12-01

A cementitious waste form, Cast Stone, is being evaluated as a possible supplemental waste form for the low activity waste (LAW) at the Hanford Site, which contains significant amounts of radioactive 99Tc and 129I, as part of the tank waste cleanup mission. To improve the retention of Tc and/or I in Cast Stone, materials with a high affinity for Tc and/or I, termed "getters," can be added to decrease the rate of contaminant release and diffusivity, and improve Cast Stone performance. A series of kinetic batch sorption experiments was performed to determine the effectiveness of the getter materials. Several Tc getters [blast furnace slag, Sn (II) apatite, SnCl2, nanoporous Sn phosphate, KMS-2 (a potassium-metal-sulfide), and Sn(II) hydroxyapatite] and I getters [layered Bi hydroxide, natural argentite mineral, synthetic argentite, Ag-impregnated carbon, and Ag-exchanged zeolite] were tested in different solution media, 18.2 MΩ DI H2O and a caustic LAW waste simulant containing 6.5 M Na or 7.8 M Na. The experiments were conducted at room temperature in the presence or absence of air. Results indicated that most Tc getters (with the exception of KMS-2) performed better in the DI H2O solution than in the 6.5 and 7.8 M Na LAW simulant. In addition, Tc sequestration may be affected by the presence of other redox sensitive elements that were present in the LAW simulant, such as Cr. The Tc getter materials have been examined through various solid-state characterization techniques such as XRD, SEM/EDS, XANES and EXAFS which provided evidence for plausible mechanisms of aqueous Tc removal. The results indicated that the Tc precipitates differ depending on the getter material and that Tc(VII) is reduced to Tc(IV) in most of the getters but to a differing extents. For the I getters, Ag-exchanged zeolite and synthetic argentite were the most effective ones. The other I getters showed limited effectiveness for sorbing I under the high ionic strength and caustic

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance

APOA5 -1131T>C and APOC3 -455T>C polymorphisms are associated with an increased risk of coronary heart disease.

PubMed

Sun, Y; Zhou, R B; Chen, D M

2015-12-28

The aim of this study was to investigate correlations between apolipoprotein A-V (APOA5) -1131T>C and apolipoprotein C-III (APOC3) -455T>C polymorphisms and coronary heart disease (CHD). PubMed, Ovid, Cochrane Library, Embase, China National Knowledge Infrastructure, and Wanfang databases were searched using combinations of keywords relating to these polymorphisms and CHD. Studies retrieved from database searches were screened using our stringent inclusion and exclusion criteria, and Comprehensive Meta-Analysis Version 2.0 software was used for statistical analyses. In total, 115 studies were initially retrieved and after further selection, 11 were included in the meta-analysis. These 11 articles comprised 4840 patients with CHD in the case group and 4913 healthy participants in the control group. Meta-analysis revealed that APOA5 -1131T>C and APOC3 -455T>C polymorphisms increased CHD risk. In addition, subgroup analysis by ethnicity showed that while the -1131T>C polymorphism elevated the risk of CHD in the Caucasian population under both allelic and dominant models, this increased risk was observed only under a dominant model in the Asian population. The results of our meta-analysis point to a strong link between both APOA5 -1131T>C and APOC3 -455T>C polymorphisms and an increased risk of CHD. Thus, these polymorphisms constitute important predictive indicators of CHD susceptibility.

Data-Driven Disease Forecasting

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

Generous, Nicholas

If disease outbreaks could be forecasted like the weather, communities could set up protective measures to mitigate their impact. At Los Alamos National Laboratory, scientists are improving disease-forecasting mathematical models by using clinical data--as well as internet data sources such as Wikipedia, Twitter, and Google--and coupling it with satellite imagery. The goal is to better understanding how diseases spread and, eventually, forecast disease outbreaks.

Tc-NGA imaging in liver transplantation: preliminary clinical experience

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

Woodle, E.S.; Ward, R.E.; Stadalnik, R.C.

1989-03-01

Technetium-99m galactosyl-neoglycoalbumin (Tc-NGA) is a new liver imaging agent that binds to hepatic-binding protein, a hepatocyte-specific membrane receptor. The purpose of this study was to determine the potential of Tc-NGA imaging in clinical liver transplantation. A total of 25 studies were performed in nine patients. Imaging studies performed in the early posttransplant period in patients with good hepatic allograft function revealed diffuse patchiness in tracer distribution, a manifestation of preservation damage. Left lobar infarction was demonstrated within a few hours of ischemic injury. Right posterior segmental infarction was seen in another patient. Comparison of kinetic, clinical, and biochemical data revealedmore » good correlation between hepatic allograft function and Tc-NGA kinetics. Major kinetic alterations were noted during periods of preservation injury, hepatic infarction, and acute rejection. These studies indicate: (1) major alterations in Tc-NGA kinetics occur during preservation injury, hepatic infarction, and acute rejection, and (2) Tc-NGA kinetic data appear to provide an accurate reflection of hepatic allograft function. Tc-NGA imaging has the advantages of being noninvasive and of utilizing standard nuclear medicine instrumentation, including portable imaging devices. In conclusion, Tc-NGA imaging provides a promising noninvasive approach for evaluation of liver function in patients undergoing hepatic transplantation.« less

Assimilation of Wave Imaging Radar Observations for Real-Time Wave-by-Wave Forecasting

NASA Astrophysics Data System (ADS)

Haller, M. C.; Simpson, A. J.; Walker, D. T.; Lynett, P. J.; Pittman, R.; Honegger, D.

2016-02-01

It has been shown in various studies that a controls system can dramatically improve Wave Energy Converter (WEC) power production by tuning the device's oscillations to the incoming wave field, as well as protect WEC devices by decoupling them in extreme wave conditions. A requirement of the most efficient controls systems is a phase-resolved, "deterministic" surface elevation profile, alerting the device to what it will experience in the near future. The current study aims to demonstrate a deterministic method of wave forecasting through the pairing of an X-Band marine radar with a predictive Mild Slope Equation (MSE) wave model. Using the radar as a remote sensing technique, the wave field up to 1-4 km surrounding a WEC device can be resolved. Individual waves within the radar scan are imaged through the contrast between high intensity wave faces and low intensity wave troughs. Using a recently developed method, radar images are inverted into the radial component of surface slope, shown in the figure provided using radar data from Newport, Oregon. Then, resolved radial slope images are assimilated into the MSE wave model. This leads to a best-fit model hindcast of the waves within the domain. The hindcast is utilized as an initial condition for wave-by-wave forecasting with a target forecast horizon of 3-5 minutes (tens of wave periods). The methodology is currently being tested with synthetic data and comparisons with field data are imminent.

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

77 FR 54908 - TC Offshore, LLC; Notice Establishing Deadline for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-06

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. RP12-908-000] TC Offshore, LLC; Notice Establishing Deadline for Comments On August 29, 2012, TC Offshore, LLC (TC Offshore... is hereby given that participants in the captioned proceedings may file comments to TC Offshsore's...

Benchmark experiment for the cross section of the 100Mo(p,2n)99mTc and 100Mo(p,pn)99Mo reactions

NASA Astrophysics Data System (ADS)

Takács, S.; Ditrói, F.; Aikawa, M.; Haba, H.; Otuka, N.

2016-05-01

As nuclear medicine community has shown an increasing interest in accelerator produced 99mTc radionuclide, the possible alternative direct production routes for producing 99mTc were investigated intensively. One of these accelerator production routes is based on the 100Mo(p,2n)99mTc reaction. The cross section of this nuclear reaction was studied by several laboratories earlier but the available data-sets are not in good agreement. For large scale accelerator production of 99mTc based on the 100Mo(p,2n)99mTc reaction, a well-defined excitation function is required to optimise the production process effectively. One of our recent publications pointed out that most of the available experimental excitation functions for the 100Mo(p,2n)99mTc reaction have the same general shape while their amplitudes are different. To confirm the proper amplitude of the excitation function, results of three independent experiments were presented (Takács et al., 2015). In this work we present results of a thick target count rate measurement of the Eγ = 140.5 keV gamma-line from molybdenum irradiated by Ep = 17.9 MeV proton beam, as an integral benchmark experiment, to prove the cross section data reported for the 100Mo(p,2n)99mTc and 100Mo(p,pn)99Mo reactions in Takács et al. (2015).

Rebuttal of "Polar bear population forecasts: a public-policy forecasting audit"

USGS Publications Warehouse

Amstrup, Steven C.; Caswell, Hal; DeWeaver, Eric; Stirling, Ian; Douglas, David C.; Marcot, Bruce G.; Hunter, Christine M.

2009-01-01

Observed declines in the Arctic sea ice have resulted in a variety of negative effects on polar bears (Ursus maritimus). Projections for additional future declines in sea ice resulted in a proposal to list polar bears as a threatened species under the United States Endangered Species Act. To provide information for the Department of the Interior's listing-decision process, the US Geological Survey (USGS) produced a series of nine research reports evaluating the present and future status of polar bears throughout their range. In response, Armstrong et al. [Armstrong, J. S., K. C. Green, W. Soon. 2008. Polar bear population forecasts: A public-policy forecasting audit. Interfaces 38(5) 382–405], which we will refer to as AGS, performed an audit of two of these nine reports. AGS claimed that the general circulation models upon which the USGS reports relied were not valid forecasting tools, that USGS researchers were not objective or lacked independence from policy decisions, that they did not utilize all available information in constructing their forecasts, and that they violated numerous principles of forecasting espoused by AGS. AGS (p. 382) concluded that the two USGS reports were "unscientific and inconsequential to decision makers." We evaluate the AGS audit and show how AGS are mistaken or misleading on every claim. We provide evidence that general circulation models are useful in forecasting future climate conditions and that corporate and government leaders are relying on these models to do so. We clarify the strict independence of the USGS from the listing decision. We show that the allegations of failure to follow the principles of forecasting espoused by AGS are either incorrect or are based on misconceptions about the Arctic environment, polar bear biology, or statistical and mathematical methods. We conclude by showing that the AGS principles of forecasting are too ambiguous and subjective to be used as a reliable basis for auditing scientific

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.

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

NASA Astrophysics Data System (ADS)

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller

Combining forecast weights: Why and how?

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

2012-09-01

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

Case Study of Hurricane Felix (2007) Rapid Intensification

NASA Astrophysics Data System (ADS)

Colon-Pagan, I. C.; Davis, C. A.; Holland, G. J.

2010-12-01

The forecasting of tropical cyclones (TC) rapid intensification (RI) is one of the most challenging problems that the operational community experiences. Research advances leading to improvements in predicting this phenomenon would help government agencies make decisions that could reduce the impact on communities that are so often affected by these weather-related events. It has been proposed that TC RI is associated to various factors, including high sea-surface temperatures, weak vertical wind shear, and the ratio of inertial to static stability, which improves the conversion of diabatic heating into circulation. While a cyclone develops, the size of the region of high inertial stability (IS) decreases whereas the magnitude of IS increases. However, it’s unknown whether this is a favorable condition or a result of RI occurrences. The purpose of this research, therefore, is to determine if the IS follows, leads or changes in sync with the intensity change by studying Hurricane Felix (2007) RI phase. Results show a trend of increasing IS before the RI stage, followed by an expansion of the region of high IS. This episode is eventually followed by a decrease in both the intensity and region of positive IS, while the maximum wind speed intensity of the TC diminished. Therefore, we propose that monitoring the IS may provide a forecast tool to determine RI periods. Other parameters, such as static stability, tangential wind, and water vapor mixing ratio may help identify other features of the storm, such as circulation and eyewall formation. The inertial stability (IS) trend during the period of rapid intensification, which occurred between 00Z and 06Z of September 3rd. Maximum values of IS were calculated before and during this period of RI within a region located 30-45 km from the center. In fact, this region could represent the eye-wall of Hurricane Felix.

Potential predictability and forecast skill in ensemble climate forecast: the skill-persistence rule

NASA Astrophysics Data System (ADS)

Jin, Y.; Rong, X.; Liu, Z.

2017-12-01

This study investigates the factors that impact the forecast skill for the real world (actual skill) and perfect model (perfect skill) in ensemble climate model forecast with a series of fully coupled general circulation model forecast experiments. It is found that the actual skill of sea surface temperature (SST) in seasonal forecast is substantially higher than the perfect skill on a large part of the tropical oceans, especially the tropical Indian Ocean and the central-eastern Pacific Ocean. The higher actual skill is found to be related to the higher observational SST persistence, suggesting a skill-persistence rule: a higher SST persistence in the real world than in the model could overwhelm the model bias to produce a higher forecast skill for the real world than for the perfect model. The relation between forecast skill and persistence is further examined using a first-order autoregressive model (AR1) analytically for theoretical solutions and numerically for analogue experiments. The AR1 model study shows that the skill-persistence rule is strictly valid in the case of infinite ensemble size, but can be distorted by the sampling error and non-AR1 processes.

Forecasting volcanic unrest using seismicity: The good, the bad and the time consuming

NASA Astrophysics Data System (ADS)

Salvage, Rebecca; Neuberg, Jurgen W.

2013-04-01

Volcanic eruptions are inherently unpredictable in nature, with scientists struggling to forecast the type and timing of events, in particular in real time scenarios. Current understanding suggests that the use of statistical patterns within precursory datasets of seismicity prior to eruptive events could hold the potential to be used as real time forecasting tools. They allow us to determine times of clear deviation in data, which might be indicative of volcanic unrest. The identification of low frequency seismic swarms and the acceleration of this seismicity prior to observed volcanic unrest may be key in developing forecasting tools. The development of these real time forecasting models which can be implemented at volcano observatories is of particular importance since the identification of early warning signals allows danger to the proximal population to be minimized. We concentrate on understanding the significance and development of these seismic swarms as unrest develops at the volcano. In particular, analysis of accelerations in event rate, amplitude and energy rates released by seismicity prior to eruption suggests that these are important indicators of developing unrest. Real time analysis of these parameters simultaneously allows possible improvements to forecasting models. Although more time and computationally intense, cross correlation techniques applied to continuous seismicity prior to volcanic unrest scenarios allows all significant seismic events to be analysed, rather than only those which can be detected by an automated identification system. This may allow a more accurate forecast since all precursory seismicity can be taken into account. In addition, the classification of seismic events based on spectral characteristics may allow us to isolate individual types of signals which are responsible for certain types of unrest. In this way, we may be able to better forecast the type of eruption that may ensue, or at least some of its prevailing

The Eruption Forecasting Information System: Volcanic Eruption Forecasting Using Databases

NASA Astrophysics Data System (ADS)

Ogburn, S. E.; Harpel, C. J.; Pesicek, J. D.; Wellik, J.

2016-12-01

Forecasting eruptions, including the onset size, duration, location, and impacts, is vital for hazard assessment and risk mitigation. The Eruption Forecasting Information System (EFIS) project is a new initiative of the US Geological Survey-USAID Volcano Disaster Assistance Program (VDAP) and will advance VDAP's ability to forecast the outcome of volcanic unrest. The project supports probability estimation for eruption forecasting by creating databases useful for pattern recognition, identifying monitoring data thresholds beyond which eruptive probabilities increase, and for answering common forecasting questions. A major component of the project is a global relational database, which contains multiple modules designed to aid in the construction of probabilistic event trees and to answer common questions that arise during volcanic crises. The primary module contains chronologies of volcanic unrest. This module allows us to query eruption chronologies, monitoring data, descriptive information, operational data, and eruptive phases alongside other global databases, such as WOVOdat and the Global Volcanism Program. The EFIS database is in the early stages of development and population; thus, this contribution also is a request for feedback from the community. Preliminary data are already benefitting several research areas. For example, VDAP provided a forecast of the likely remaining eruption duration for Sinabung volcano, Indonesia, using global data taken from similar volcanoes in the DomeHaz database module, in combination with local monitoring time-series data. In addition, EFIS seismologists used a beta-statistic test and empirically-derived thresholds to identify distal volcano-tectonic earthquake anomalies preceding Alaska volcanic eruptions during 1990-2015 to retrospectively evaluate Alaska Volcano Observatory eruption precursors. This has identified important considerations for selecting analog volcanoes for global data analysis, such as differences between

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis(2008)

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Tao, W.-K.; Lau, W. K.; Atlas, R.

2010-01-01

Very severe cyclonic storm Nargis devastated Burma (Myanmar) in May 2008, caused tremendous damage and numerous fatalities, and became one of the 10 deadliest tropical cyclones (TCs) of all time. To increase the warning time in order to save lives and reduce economic damage, it is important to extend the lead time in the prediction of TCs like Nargis. As recent advances in high-resolution global models and supercomputing technology have shown the potential for improving TC track and intensity forecasts, the ability of a global mesoscale model to predict TC genesis in the Indian Ocean is examined in this study with the aim of improving simulations of TC climate. High-resolution global simulations with real data show that the initial formation and intensity variations of TC Nargis can be realistically predicted up to 5 days in advance. Preliminary analysis suggests that improved representations of the following environmental conditions and their hierarchical multiscale interactions were the key to achieving this lead time: (1) a westerly wind burst and equatorial trough, (2) an enhanced monsoon circulation with a zero wind shear line, (3) good upper-level outflow with anti-cyclonic wind shear between 200 and 850 hPa, and (4) low-level moisture convergence.

75 FR 5855 - Proposed Collection; Comment Request for Form 8038-TC

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-04

... 8038-TC AGENCY: Internal Revenue Service (IRS), Treasury. ACTION: Notice and request for comments... comments concerning Form 8038-TC, Information Return for Tax Credit Bonds. DATES: Written comments should...: Form 8038-TC. Abstract: Form 8038-TC will be used by issuers of qualified tax- exempt credit bonds...

Tc-99m Labeled carrier for imaging

DOEpatents

Henze, Eberhard

1984-01-01

Novel radionuclide imaging agents, having particular application for lymphangiography are provided by non-covalently binding Tc-99m to a pharmaceutically acceptable cross-linked polysaccharide. Upon injection of the Tc-99m labeled polysaccharide into the blood stream, optimum contrast can be obtained within one hour.

Hurricane Forecasts with a Global Mesoscale-resolving Model on the NASA Columbia Supercomputer Preliminary Simulations of Hurricane Katrina (2005)

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Atlas, R.; Reale, O.; Chern, J.-D.; Li, S.-J.; Lee, T.; Chang, J.; Henze, C.; Yeh, K.-S.

2006-01-01

It is known that the General Circulation Models (GCMs) have sufficient resolution to accurately simulate hurricane near-eye structure and intensity. To overcome this limitation, the mesoscale-resolving finite-element GCM (fvGCM) has been experimentally deployed on the NASA Columbia supercomputer, and its performance is evaluated choosing hurricane Katrina as an example in this study. On late August 2005 Katrina underwent two stages of rapid intensification and became the sixth most intense hurricane in the Atlantic. Six 5-day simulations of Katrina at both 0.25 deg and 0.125 deg show comparable track forecasts, but the 0,125 deg runs provide much better intensity forecasts, producing center pressure with errors of only +/- 12 hPa. The 0.125 deg simulates better near-eye wind distributions and a more realistic average intensification rate. A convection parameterization (CP) is one of the major limitations in a GCM, the 0.125 deg run with CP disabled produces very encouraging results.

Statistical Earthquake Focal Mechanism Forecasts

NASA Astrophysics Data System (ADS)

Kagan, Y. Y.; Jackson, D. D.

2013-12-01

The new whole Earth focal mechanism forecast, based on the GCMT catalog, has been created. In the present forecast, the sum of normalized seismic moment tensors within 1000 km radius is calculated and the P- and T-axes for the focal mechanism are evaluated on the basis of the sum. Simultaneously we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms. This average angle shows tectonic complexity of a region and indicates the accuracy of the prediction. The method was originally proposed by Kagan and Jackson (1994, JGR). Recent interest by CSEP and GEM has motivated some improvements, particularly to extend the previous forecast to polar and near-polar regions. The major problem in extending the forecast is the focal mechanism calculation on a spherical surface. In the previous forecast as our average focal mechanism was computed, it was assumed that longitude lines are approximately parallel within 1000 km radius. This is largely accurate in the equatorial and near-equatorial areas. However, when one approaches the 75 degree latitude, the longitude lines are no longer parallel: the bearing (azimuthal) difference at points separated by 1000 km reach about 35 degrees. In most situations a forecast point where we calculate an average focal mechanism is surrounded by earthquakes, so a bias should not be strong due to the difference effect cancellation. But if we move into polar regions, the bearing difference could approach 180 degrees. In a modified program focal mechanisms have been projected on a plane tangent to a sphere at a forecast point. New longitude axes which are parallel in the tangent plane are corrected for the bearing difference. A comparison with the old 75S-75N forecast shows that in equatorial regions the forecasted focal mechanisms are almost the same, and the difference in the forecasted focal mechanisms rotation angle is close to zero. However, though the forecasted focal mechanisms are similar

An Evaluation of the NOAA Climate Forecast System Subseasonal Forecasts

NASA Astrophysics Data System (ADS)

Mass, C.; Weber, N.

2016-12-01

This talk will describe a multi-year evaluation of the 1-5 week forecasts of the NOAA Climate Forecasting System (CFS) over the globe, North America, and the western U.S. Forecasts are evaluated for both specific times and for a variety of time-averaging periods. Initial results show a loss of predictability at approximately three weeks, with sea surface temperature retaining predictability longer than atmospheric variables. It is shown that a major CFS problem is an inability to realistically simulate propagating convection in the tropics, with substantial implications for midlatitude teleconnections and subseasonal predictability. The inability of CFS to deal with tropical convection will be discussed in connection with the prediction of extreme climatic events over the midlatitudes.

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

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.

Determining relevant parameters for a statistical tropical cyclone genesis tool based upon global model output

NASA Astrophysics Data System (ADS)

Halperin, D.; Hart, R. E.; Fuelberg, H. E.; Cossuth, J.

2013-12-01

Predicting tropical cyclone (TC) genesis has been a vexing problem for forecasters. While the literature describes environmental conditions which are necessary for TC genesis, predicting if and when a specific disturbance will organize and become a TC remains a challenge. As recently as 5-10 years ago, global models possessed little if any skill in forecasting TC genesis. However, due to increased resolution and more advanced model parameterizations, we have reached the point where global models can provide useful TC genesis guidance to operational forecasters. A recent study evaluated five global models' ability to predict TC genesis out to four days over the North Atlantic basin (Halperin et al. 2013). The results indicate that the models are indeed able to capture the genesis time and location correctly a fair percentage of the time. The study also uncovered model biases. For example, probability of detection and false alarm rate varies spatially within the basin. Also, as expected, the models' performance decreases with increasing lead time. In order to explain these and other biases, it is useful to analyze the model-indicated genesis events further to determine whether or not there are systematic differences between successful forecasts (hits), false alarms, and miss events. This study will examine composites of a number of physically-relevant environmental parameters (e.g., magnitude of vertical wind shear, aerially averaged mid-level relative humidity) and disturbance-based parameters (e.g., 925 hPa maximum wind speed, vertical alignment of relative vorticity) among each TC genesis event classification (i.e., hit, false alarm, miss). We will use standard statistical tests (e.g., Student's t test, Mann-Whitney-U Test) to calculate whether or not any differences are statistically significant. We also plan to discuss how these composite results apply to a few illustrative case studies. The results may help determine which aspects of the forecast are (in

78 FR 40824 - Proposed Collection; Comment Request for Form 8038-TC

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-08

... 8038-TC AGENCY: Internal Revenue Service (IRS), Treasury. ACTION: Notice and request for comments... Form 8038-TC, Information Return for Tax Credit Bonds. DATES: Written comments should be received on or...-TC. Abstract: Form 8038-TC will be used by issuers of qualified tax- exempt credit bonds, including...

Association of hyperfunctioning thyroid adenoma with thyroid cancer presenting as "trapping only" nodule at 99mTcO4- scintigraphy.

PubMed

dell'Erba, L; Gerundini, P; Caputo, M; Bagnasco, M

2003-11-01

Rarely may a non-hyperfunctioning thyroid nodule present as "hot" at Technetium-99m pertechnetate (99mTcO4-) and "cold" at radioiodine scintigraphy at late acquisitions. We report the case of a hyperthyroid female patient whose 99mTcO4- scintigraphy showed two "hot" nodules, whereas Iodide-131 (131I-) revealed a lack of indicator uptake by the larger, and intense uptake by the smaller nodule. The patient underwent surgery: histology demonstrated that the larger nodule, mismatched at pertechnetate vs iodine scintigraphy, was a papillary carcinoma. Our suggestion is to perform thyroid scintigraphy with radioiodine in hyperthyroid patients with more than one nodule concentrating pertechnetate, especially when an ultrasonographic pattern possibly suspect for malignancy is present.

Forecast communication through the newspaper Part 1: Framing the forecaster

NASA Astrophysics Data System (ADS)

Harris, Andrew J. L.

2015-04-01

This review is split into two parts both of which address issues of forecast communication of an environmental disaster through the newspaper during a period of crisis. The first part explores the process by which information passes from the scientist or forecaster, through the media filter, to the public. As part of this filter preference, omission, selection of data, source, quote and story, as well as placement of the same information within an individual piece or within the newspaper itself, can serve to distort the message. The result is the introduction of bias and slant—that is, the message becomes distorted so as to favor one side of the argument against another as it passes through the filter. Bias can be used to support spin or agenda setting, so that a particular emphasis becomes placed on the story which exerts an influence on the reader's judgment. The net result of the filter components is either a negative (contrary) or positive (supportive) frame. Tabloidization of the news has also resulted in the use of strong, evocative, exaggerated words, headlines and images to support a frame. I illustrate these various elements of the media filter using coverage of the air space closure due to the April 2010 eruption of Eyjafjallajökull (Iceland). Using the British press coverage of this event it is not difficult to find examples of all media filter elements, application of which resulted in bias against the forecast and forecaster. These actors then became named and blamed. Within this logic, it becomes only too easy for forecasters and scientists to be framed in a negative way through blame culture. The result is that forecast is framed in such a way so as to cause the forecaster to be blamed for all losses associated with the loss-causing event. Within the social amplification of risk framework (SARF), this can amplify a negative impression of the risk, the event and the response. However, actions can be taken to avoid such an outcome. These actions

Advancing atmospheric river forecasts into subseasonal-to-seasonal time scales

NASA Astrophysics Data System (ADS)

Baggett, Cory F.; Barnes, Elizabeth A.; Maloney, Eric D.; Mundhenk, Bryan D.

2017-07-01

Atmospheric rivers are elongated plumes of intense moisture transport that are capable of producing extreme and impactful weather. Along the West Coast of North America, they occasionally cause considerable mayhem—delivering flooding rains during periods of heightened activity and desiccating droughts during periods of reduced activity. The intrinsic chaos of the atmosphere makes the prediction of atmospheric rivers at subseasonal-to-seasonal time scales (3 to 5 weeks) an inherently difficult task. We demonstrate here that the potential exists to advance forecast lead times of atmospheric rivers into subseasonal-to-seasonal time scales through knowledge of two of the atmosphere's most prominent oscillations, the Madden-Julian oscillation (MJO) and the quasi-biennial oscillation (QBO). Strong MJO and QBO activity modulates the frequency at which atmospheric rivers strike—offering an opportunity to improve subseasonal-to-seasonal forecast models and thereby skillfully predict atmospheric river activity up to 5 weeks in advance.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

Forecasting Lightning Threat using Cloud-resolving Model Simulations

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.; Goodman, S. J.; LaCasse, K. M.; Cecil, D. J.

2009-01-01

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\\dgc\\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating

Uncertainties in Forecasting Streamflow using Entropy Theory

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

Tc-99m Glu-Cys-Gly-His-Gly-Lys (ECG-HGK), a novel Tc-99m labeled hexapeptide for molecular tumor imaging.

PubMed

Kim, Dae-Weung; Kim, Myoung Hyoun; Kim, Chang Guhn

2016-03-01

Domain 5 of kinin-free high molecular weight kininogen inhibits the adhesion of many tumor cell lines, and it has been reported that the histidine-glycine-lysine (HGK)-rich region might be responsible for inhibition of cell adhesion. The authors developed HGK-containing hexapeptide, glutamic acid-cysteine-glycine (ECG)-HGK, and evaluated the utility of Tc-99m ECG-HGK for tumor imaging. Hexapeptide, ECG-HGK was synthesized using Fmoc solid-phase peptide synthesis. Radiolabeling efficiency was evaluated. The uptake of Tc-99m ECG-HGK within HT-1080 cells was evaluated in vitro. In HT-1080 tumor-bearing mice, gamma imaging and biodistribution studies were performed. The complexes Tc-99m ECG-HGK was prepared in high yield. The uptake of Tc-99m ECG-HGK within the HT-1080 tumor cells had been demonstrated by in vitro studies. The gamma camera imaging in the murine model showed that Tc-99m ECG-HGK was accumulated substantially in the HT-1080 tumor (tumor-to-muscle ratio = 5.7 ± 1.4 at 4 h), and the tumoral uptake was blocked by the co-injection of excess HGK (tumor-to-muscle ratio = 2.8 ± 0.6 at 4 h). In the present study, Tc-99m ECG-HGK was developed as a new tumor imaging agents. Our in vitro and in vivo studies revealed specific function of Tc-99m ECG-HGK for tumor imaging. Copyright © 2016 John Wiley & Sons, Ltd.

PREFACE: 2013 Joint IMEKO (International Measurement Confederation) TC1-TC7-TC13 Symposium: Measurement Across Physical and Behavioural Sciences

NASA Astrophysics Data System (ADS)

Battista Rossi, Giovanni; Crenna, Francesco; Belotti, Vittorio

2013-09-01

The 2013 Joint IMEKO (International Measurement Confederation) TC1-C7-TC13 was organised by the University of Genova - DIME/MEC, Measurement Laboratory, Italy, on 4-6 September 2013. The work of this symposium is reported in this volume. The scope of the symposium includes the main topics covered by the above Technical Committees: TC1 Education and Training in Measurement and Instrumentation TC7 Measurement Science TC13 Measurements in Biology and Medicine This is in keeping with the tradition set by the previous events of this well established series. There has been a special focus on measurement across physical and behavioural sciences, with the aim of highlighting the interdisciplinary character of measurement science and of promoting constructive interactions with scientists in other disciplines. The discussion was introduced by keynote lectures on measurement challenges in psychophysics, psychometrics and quantum physics. The symposium was attended by experts working in these areas from 18 countries, including USA, Australia and Japan, and provided a useful forum for them to share and exchange their work and ideas. In total over sixty papers are included in the volume, organised according to the presentation sessions. Each paper was independently peer-reviewed by two reviewers from a distinguished international panel. The Symposium was held in Genova, which was the European Capital of Culture in 2004, and took place in Palazzo Ducale, an important historical building whose construction started in the 13th century, and that has been the house of the Duke of Genova from the 14th century. Genova, whose name comes from the Latin word 'Janua' (meaning 'door', as January is the door month of the year), has been regarded over the centuries as a door connecting Europe with the different countries and cultures of the Mediterranean basin and thus was an appropriate site for an international symposium involving different and new scientific visions and approaches to

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

SCDFT Study of High Tc Nitride Superconductors

NASA Astrophysics Data System (ADS)

Arita, R.

Based on the density functional theory for superconductors (SCDFT), we study the pairing mechanism of the layered nitride superconductors, β-LixMNCl (M=Zr, Hf). Recently, it has been shown that SCDFT reproduces experimental superconducting transition temperatures (Tc) of conventional superconductors very accurately. Here we use SCDFT as a "litmus paper" to determine whether the system is a conventional or unconventional superconductor. We show that Tc estimated by SCDFT is less than half of the experimental Tc and its doping dependence is opposite to that observed in the experiments. The present result suggests that β- LixMNCl is not a Migdal-Eliashberg type superconductor.

Increased breast density correlates with the proliferation-seeking radiotracer (99m)Tc(V)-DMSA uptake in florid epithelial hyperplasia and in mixed ductal carcinoma in situ with invasive ductal carcinoma but not in pure invasive ductal carcinoma or in mild epithelial hyperplasia.

PubMed

Papantoniou, Vassilios; Valsamaki, Pipitsa; Sotiropoulou, Evangelia; Tsaroucha, Angeliki; Tsiouris, Spyridon; Sotiropoulou, Maria; Marinopoulos, Spyridon; Kounadi, Evangelia; Karianos, Theodore; Fothiadaki, Athina; Archontaki, Aikaterini; Syrgiannis, Konstantinos; Ptohis, Nikolaos; Makris, Nikolaos; Limouris, Georgios; Antsaklis, Aris

2011-10-01

The purpose of this study was to assess the relationship of mammographic breast density (BD) and cell proliferation/focal adhesion kinase activation-seeking radiotracer technetium 99m pentavalent dimercaptosuccinic acid (99mTc(V)-DMSA) uptake in women with different breast histologies, that is, mild epithelial hyperplasia (MEH), florid epithelial hyperplasia (FEH), mixed ductal carcinoma in situ with invasive ductal carcinoma (DCIS + IDC), and pure IDC. Fifty-five women with histologically confirmed mammary pathologies were submitted preoperatively to mammography and 99mTc(V)-DMSA scintimammography. The percentage and intensity of 99mTc(V)-DMSA uptake and the percentage of BD were calculated by computer-assisted methods and compared (t-test) between the breast pathologies. In breasts with increased BD, FEH and DCIS + IDC were found. On the contrary, pure IDC and MEH were identified in breasts with significantly lower BD values. In breasts with increased 99mTc(V)-DMSA area and intensity of uptake, FEH was the main lesion found compared to all other histologies. Linear regression analysis between BD and 99mTc(V)-DMSA uptake area and intensity revealed significant coefficients of correlation (r  =  .689, p < .001 and r  =  .582, p < .001, respectively). Increased BD correlates with the presence of FEH and mixed DCIS + IDC but not with pure IDC or MEH. Its close relationship to 99mTc(V)-DMSA, which also showed an affinity to FEH, indicates that stromal microenvironment may constitute a specific substrate leading to progression to different subtypes of cancerous lesions originating from different pathways.

Forecast of geomagnetic storms using CME parameters and the WSA-ENLIL model

NASA Astrophysics Data System (ADS)

Moon, Y.; Lee, J.; Jang, S.; Na, H.; Lee, J.

2013-12-01

Intense geomagnetic storms are caused by coronal mass ejections (CMEs) from the Sun and their forecast is quite important in protecting space- and ground-based technological systems. The onset and strength of geomagnetic storms depend on the kinematic and magnetic properties of CMEs. Current forecast techniques mostly use solar wind in-situ measurements that provide only a short lead time. On the other hand, techniques using CME observations near the Sun have the potential to provide 1-3 days of lead time before the storm occurs. Therefore, one of the challenging issues is to forecast interplanetary magnetic field (IMF) southward components and hence geomagnetic storm strength with a lead-time on the order of 1-3 days. We are going to answer the following three questions: (1) when does a CME arrive at the Earth? (2) what is the probability that a CME can induce a geomagnetic storm? and (3) how strong is the storm? To address the first question, we forecast the arrival time and other physical parameters of CMEs at the Earth using the WSA-ENLIL model with three CME cone types. The second question is answered by examining the geoeffective and non-geoeffective CMEs depending on CME observations (speed, source location, earthward direction, magnetic field orientation, and cone-model output). The third question is addressed by examining the relationship between CME parameters and geomagnetic indices (or IMF southward component). The forecast method will be developed with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the physics-based models.

TRAVEL FORECASTER

NASA Technical Reports Server (NTRS)

Mauldin, L. E.

1994-01-01

Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of

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

Forecasting E > 50-MeV Proton Events with the Proton Prediction System (PPS)

NASA Astrophysics Data System (ADS)

Kahler, S. W.; White, S. M.; Ling, A. G.

2017-12-01

Forecasting solar energetic (E > 10 MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (> 50 MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E > 50-MeV proton events > 1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986 to 2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all > M5 solar X-ray flares; (2) all > 200 sfu 8800-MHz bursts with associated > M5 flares; (3) all > 500 sfu 8800-MHz bursts; and (4) all > 5000 sfu 8800-MHz bursts. For X-ray flare inputs the forecasted event peak intensities and fluences are compared with observed values. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude.

Validation of an ergonomic method to withdraw [99mTc] radiopharmaceuticals.

PubMed

Blondeel-Gomes, Sandy; Marie, Solène; Fouque, Julien; Loyeau, Sabrina; Madar, Olivier; Lokiec, François

2017-11-10

The main objective of the present work was to ensure quality of radiopharmaceuticals syringes withdrawn with a "Spinal needle/obturator In-Stopper" system. Methods: Visual examinations and physicochemical tests are performed at T0 and T+4h for [ 99m Tc]albumin nanocolloid and T+7h for [ 99m Tc]eluate, [ 99m Tc] HydroxyMethylene DiPhosphonate and [ 99m Tc]Human Serum Albumin. Microbiological validation was performed according to European pharmacopoeia. Fingertip radiation exposure was evaluated to confirm the safety of the system. Results: Results show stable visual and physicochemical properties. The integrity of the connector was not affected after 30 punctures (no cores). No microbiological contamination was found on tested syringes. Conclusion: The system could be used 30 times. The stability of syringes drawing with this method is guaranteed up to 4 hours for [ 99m Tc]albumin nanocolloid and 7 hours for [ 99m Tc]eluate, [ 99m Tc]HydroxyMethylene DisPhosphonate and [ 99m Tc]Human serum albumin. Copyright © 2017 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Comparison of 99mTc-UBI 29-41, 99mTc-Ciprofloxacin, 99mTc-Ciprofloxacin dithiocarbamate and 111In-biotin for targeting experimental Staphylococcus aureus and Escherichia coli foreign-body infections: an ex-vivo study.

PubMed

Auletta, Sveva; Baldoni, Daniela; Varani, Michela; Galli, Filippo; Hajar, Iman A; Duatti, Adriano; Ferro-Flores, Guillermina; Trampuz, Andrej; Signore, Alberto

2017-08-28

Diagnosis of implant-associated infection is challenging. Several radiopharmaceuticals have been described but direct comparisons are limited. Here we compared in vitro and in an animal model 99mTc-UBI, 99mTc-Ciprofloxacin, 99mTcN-CiproCS2 and 111In-DTPA-biotin for targeting E. coli (ATCC 25922) and S. aureus (ATCC 43335). Stability controls were performed with the labelled radiopharmaceuticals during 6 h in saline and serum. The in vitro binding to viable or killed bacteria was evaluated at 37 °C and 4 °C. For in vivo studies, Teflon cages were subcutaneously implanted in mice, followed by percutaneous infection. Biodistribution of i.v. injected radiolabelled radiopharmaceuticals were evaluated during 24 h in cages and dissected tissues. Labelling efficiency of all radiopharmaceuticals ranged between 94% and 98%, with high stability both in saline and in human serum. In vitro binding assays displayed a rapid but poor bacterial binding for all tested agents. Similar binding kinetic occurred also with heat-killed and ethanol-killed bacteria. In the tissue cage model, infection was detected at different time points: 99mTc-UBI and 99mTcN-CiproCS2 showed higher infected cage/sterile cage ratio at 24 h for both E. coli and S. aureus; 99mTc-Ciprofloxacin at 24 h for both E. coli and at 4 h for S. aureus; 111In-DTPA-biotin accumulates faster in both E. coli and S. aureus infected cages. 99mTc-UBI, 99mTcN-CiproCS2 showed poor in vitro binding but good in vivo binding to E. coli only. 111In-DTPA-biotin showed poor in vitro binding but good in vivo binding to S. aureus and poor to E. coli. 99mTc-Ciprofloxacin showed poor in vitro binding but good in vivo binding to all tested bacteria. The mechanism of accumulation in infected sites remains to be elucidated.

Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

NASA Astrophysics Data System (ADS)

O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

2015-04-01

Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

Survey of air cargo forecasting techniques

NASA Technical Reports Server (NTRS)

Kuhlthan, A. R.; Vermuri, R. S.

1978-01-01

Forecasting techniques currently in use in estimating or predicting the demand for air cargo in various markets are discussed with emphasis on the fundamentals of the different forecasting approaches. References to specific studies are cited when appropriate. The effectiveness of current methods is evaluated and several prospects for future activities or approaches are suggested. Appendices contain summary type analyses of about 50 specific publications on forecasting, and selected bibliographies on air cargo forecasting, air passenger demand forecasting, and general demand and modalsplit modeling.

Statistical evaluation of forecasts

NASA Astrophysics Data System (ADS)

Mader, Malenka; Mader, Wolfgang; Gluckman, Bruce J.; Timmer, Jens; Schelter, Björn

2014-08-01

Reliable forecasts of extreme but rare events, such as earthquakes, financial crashes, and epileptic seizures, would render interventions and precautions possible. Therefore, forecasting methods have been developed which intend to raise an alarm if an extreme event is about to occur. In order to statistically validate the performance of a prediction system, it must be compared to the performance of a random predictor, which raises alarms independent of the events. Such a random predictor can be obtained by bootstrapping or analytically. We propose an analytic statistical framework which, in contrast to conventional methods, allows for validating independently the sensitivity and specificity of a forecasting method. Moreover, our method accounts for the periods during which an event has to remain absent or occur after a respective forecast.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Balancing Flood Risk and Water Supply in California: Policy Search Combining Short-Term Forecast Ensembles and Groundwater Recharge

NASA Astrophysics Data System (ADS)

Herman, J. D.; Steinschneider, S.; Nayak, M. A.

2017-12-01

Short-term weather forecasts are not codified into the operating policies of federal, multi-purpose reservoirs, despite their potential to improve service provision. This is particularly true for facilities that provide flood protection and water supply, since the potential flood damages are often too severe to accept the risk of inaccurate forecasts. Instead, operators must maintain empty storage capacity to mitigate flood risk, even if the system is currently in drought, as occurred in California from 2012-2016. This study investigates the potential for forecast-informed operating rules to improve water supply efficiency while maintaining flood protection, combining state-of-the-art weather hindcasts with a novel tree-based policy optimization framework. We hypothesize that forecasts need only accurately predict the occurrence of a storm, rather than its intensity, to be effective in regions like California where wintertime, synoptic-scale storms dominate the flood regime. We also investigate the potential for downstream groundwater injection to improve the utility of forecasts. These hypotheses are tested in a case study of Folsom Reservoir on the American River. Because available weather hindcasts are relatively short (10-20 years), we propose a new statistical framework to develop synthetic forecasts to assess the risk associated with inaccurate forecasts. The efficiency of operating policies is tested across a range of scenarios that include varying forecast skill and additional groundwater pumping capacity. Results suggest that the combined use of groundwater storage and short-term weather forecasts can substantially improve the tradeoff between water supply and flood control objectives in large, multi-purpose reservoirs in California.

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Light intensity related to stand density in mature stands of the western white pine type

Treesearch

C. A. Wellner

1948-01-01

Where tolerance of forest trees or subordinate vegetation is a factor in management, the forester needs a simple field method of Estimating or forecasting light intensities in forest stands. The following article describes a method developed for estimating light intensity beneath the canopy in western white pine forests which may have application in other types.

Health Sciences Libraries Forecasting Information Service Trends for Researchers: Models Applicable to All Academic Libraries

ERIC Educational Resources Information Center

Cain, Timothy J.; Cheek, Fern M.; Kupsco, Jeremy; Hartel, Lynda J.; Getselman, Anna

2016-01-01

To better understand the value of current information services and to forecast the evolving information and data management needs of researchers, a study was conducted at two research-intensive universities. The methodology and planning framework applied by health science librarians at Emory University and The Ohio State University focused on…

Empirical seasonal forecasts of the NAO

NASA Astrophysics Data System (ADS)

Sanchezgomez, E.; Ortizbevia, M.

2003-04-01

We present here seasonal forecasts of the North Atlantic Oscillation (NAO) issued from ocean predictors with an empirical procedure. The Singular Values Decomposition (SVD) of the cross-correlation matrix between predictor and predictand fields at the lag used for the forecast lead is at the core of the empirical model. The main predictor field are sea surface temperature anomalies, although sea ice cover anomalies are also used. Forecasts are issued in probabilistic form. The model is an improvement over a previous version (1), where Sea Level Pressure Anomalies were first forecast, and the NAO Index built from this forecast field. Both correlation skill between forecast and observed field, and number of forecasts that hit the correct NAO sign, are used to assess the forecast performance , usually above those values found in the case of forecasts issued assuming persistence. For certain seasons and/or leads, values of the skill are above the .7 usefulness treshold. References (1) SanchezGomez, E. and Ortiz Bevia M., 2002, Estimacion de la evolucion pluviometrica de la Espana Seca atendiendo a diversos pronosticos empiricos de la NAO, in 'El Agua y el Clima', Publicaciones de la AEC, Serie A, N 3, pp 63-73, Palma de Mallorca, Spain

Interannual variability of the frequency and intensity of tropical cyclones striking the California coast

NASA Astrophysics Data System (ADS)

Mendez, F. J.; Rueda, A.; Barnard, P.; Mori, N.; Nakajo, S.; Albuquerque, J.

2016-12-01

Hurricanes hitting California have a very low ocurrence probability due to typically cool ocean temperature and westward tracks. However, damages associated to these improbable events would be dramatic in Southern California and understanding the oceanographic and atmospheric drivers is of paramount importance for coastal risk management for present and future climates. A statistical analysis of the historical events is very difficult due to the limited resolution of atmospheric and oceanographic forcing data available. In this work, we propose a combination of: (a) climate-based statistical downscaling methods (Espejo et al, 2015); and (b) a synthetic stochastic tropical cyclone (TC) model (Nakajo et al, 2014). To build the statistical downscaling model, Y=f(X), we apply a combination of principal component analysis and the k-means classification algorithm to find representative patterns from large-scale may-to-november averaged monthly anomalies of SST and thermocline depth fields in Tropical Pacific (predictor X) and the associated historical tropical cyclones in Eastern North Pacific basin (predictand Y). As data for the historical occurrence and paths of tropical cyclones are scarce, we apply a stochastic TC model which is based on a Monte Carlo simulation of the joint distribution of track, minimum sea level pressure and translation speed of the historical events in the Eastern Central Pacific Ocean. Results will show the ability of the approach to explain the interannual variability of the frequency and intensity of TCs in Southern California, which is clearly related to post El Niño Eastern Pacific and El Niño Central Pacific. References Espejo, A., Méndez, F.J., Diez, J., Medina, R., Al-Yahyai, S. (2015) Seasonal probabilistic forecasting of tropical cyclone activity in the North Indian Ocean, Journal of Flood Risk Management, DOI: 10.1111/jfr3.12197 Nakajo, S., N. Mori, T. Yasuda, and H. Mase (2014) Global Stochastic Tropical Cyclone Model Based on

Stochastic Model of Seasonal Runoff Forecasts

NASA Astrophysics Data System (ADS)

Krzysztofowicz, Roman; Watada, Leslie M.

1986-03-01

Each year the National Weather Service and the Soil Conservation Service issue a monthly sequence of five (or six) categorical forecasts of the seasonal snowmelt runoff volume. To describe uncertainties in these forecasts for the purposes of optimal decision making, a stochastic model is formulated. It is a discrete-time, finite, continuous-space, nonstationary Markov process. Posterior densities of the actual runoff conditional upon a forecast, and transition densities of forecasts are obtained from a Bayesian information processor. Parametric densities are derived for the process with a normal prior density of the runoff and a linear model of the forecast error. The structure of the model and the estimation procedure are motivated by analyses of forecast records from five stations in the Snake River basin, from the period 1971-1983. The advantages of supplementing the current forecasting scheme with a Bayesian analysis are discussed.

Type- and Subtype-Specific Influenza Forecast.

PubMed

Kandula, Sasikiran; Yang, Wan; Shaman, Jeffrey

2017-03-01

Prediction of the growth and decline of infectious disease incidence has advanced considerably in recent years. As these forecasts improve, their public health utility should increase, particularly as interventions are developed that make explicit use of forecast information. It is the task of the research community to increase the content and improve the accuracy of these infectious disease predictions. Presently, operational real-time forecasts of total influenza incidence are produced at the municipal and state level in the United States. These forecasts are generated using ensemble simulations depicting local influenza transmission dynamics, which have been optimized prior to forecast with observations of influenza incidence and data assimilation methods. Here, we explore whether forecasts targeted to predict influenza by type and subtype during 2003-2015 in the United States were more or less accurate than forecasts targeted to predict total influenza incidence. We found that forecasts separated by type/subtype generally produced more accurate predictions and, when summed, produced more accurate predictions of total influenza incidence. These findings indicate that monitoring influenza by type and subtype not only provides more detailed observational content but supports more accurate forecasting. More accurate forecasting can help officials better respond to and plan for current and future influenza activity. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spectroscopic Properties of Tc(I) Tricarbonyl Species Relevant to the Hanford Tank Waste

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

Levitskaia, Tatiana G.; Andersen, Amity; Chatterjee, Sayandev

2015-12-04

Technetium-99 (Tc) exists predominately in soluble forms in the liquid supernatant and salt cake fractions of the nuclear tank waste stored at the U.S. DOE Hanford Site. In the strongly alkaline environments prevalent in the tank waste, its dominant chemical form is pertechnetate (TcO4-, oxidation state +7). However, attempts to remove Tc from the Hanford tank waste using ion-exchange processes specific to TcO 4 - only met with limited success, particularly processing tank waste samples containing elevated concentrations of organic complexants. This suggests that a significant fraction of the soluble Tc can be present as non-pertechnetate low-valent Tc (oxidation statemore » < +7) (non-pertechnetate). The chemical identities of these non-pertechnetate species are poorly understood. Previous analysis of the SY-101 and SY-103 tank waste samples provided strong evidence that non-pertechnetate can be comprised of [Tc(CO) 3] + complexes containing Tc in oxidation state +1 (Lukens et al. 2004). During the last two years, our team has expanded this work and demonstrated that high-ionic-strength solutions typifying tank waste supernatants promote oxidative stability of the [Tc(CO) 3] + species (Rapko et al. 2013; Levitskaia et al. 2014). It also was observed that high-ionic-strength alkaline matrices stabilize Tc(VI) and potentially Tc(IV) oxidation states, particularly in presence organic chelators, suggesting that the relevant Tc compounds can serve as important redox intermediates facilitating the reduction of Tc(VII) to Tc(I). Designing strategies for effective Tc processing, including separation and immobilization, necessitates understanding the molecular structure of these non-pertechnetate species and their identification in the actual tank waste samples. To-date, only limited information exists regarding the nature and characterization of the Tc(I), Tc(IV), and Tc(VI) species. One objective of this project is to identify the form of non-pertechnetate in the

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

Modulation of Subseasonal Tropical Cyclone Genesis In The Western North Pacific By Wave Activities

NASA Astrophysics Data System (ADS)

Gao, Jianyun; Cheung, Kevin K. W.

2017-04-01

Tropical cyclone (TC) activity is well known to possess variability on multiple timescales, ranging from inter-decadal to intraseasonal. In this study, the subseasonal variability of TC genesis in the western North Pacific (WNP) is examined during summer (May-October) for the period of 1979-2015. In particular, clustering of TC activity within subseasonal timescale is the focus. First, three phases (active, normal and inactive phases) of TC clustering are defined based on the statistics of genesis frequency. Then the modes of subseasonal modulation of these three phases by intraseasonal (30-60-day) oscillation (ISO), biweekly (10-20-day) oscillation (BWO), and the convectively coupled equatorial waves (CCEW), including Rossby, Kelvin, and mixed Rossby-gravity and tropical depression-type waves are considered. It is found that the embedding large-scale circulation is significantly different between the inactive phase and the other phases. Further, the intensities and propagation phases of the ISO, BWO and CCEW play different roles to modulate TC genesis frequency during the active and normal phase. Considering the lag correlation of these subseasonal modulation modes and TC genesis, it is possible to construct a statistical model for the purpose of extended-range forecasting of subseasonal variability of TC occurrence over the WNP.

Econometrics 101: forecasting demystified

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

Crow, R.T.

1980-05-01

Forecasting by econometric modeling is described in a commonsense way which omits much of the technical jargon. A trend of continuous growth is no longer an adequate forecasting tool. Today's forecasters must consider rapid changes in price, policies, regulations, capital availability, and the cost of being wrong. A forecasting model is designed by identifying future influences on electricity purchases and quantifying their relationships to each other. A record is produced which can be evaluated and used to make corrections in the models. Residential consumption is used to illustrate how this works and to demonstrate how power consumption is also relatedmore » to the purchase and use of equipment. While models can quantify behavioral relationships, they cannot account for the impacts of non-price factors because of limited data. (DCK)« less

Impact of CAMEX-4 Data Sets for Hurricane Forecasts using a Global Model

NASA Technical Reports Server (NTRS)

Kamineni, Rupa; Krishnamurti, T. N.; Pattnaik, S.; Browell, Edward V.; Ismail, Syed; Ferrare, Richard A.

2005-01-01

This study explores the impact on hurricane data assimilation and forecasts from the use of dropsondes and remote-sensed moisture profiles from the airborne Lidar Atmospheric Sensing Experiment (LASE) system. We show that the use of these additional data sets, above those from the conventional world weather watch, has a positive impact on hurricane predictions. The forecast tracks and intensity from the experiments show a marked improvement compared to the control experiment where such data sets were excluded. A study of the moisture budget in these hurricanes showed enhanced evaporation and precipitation over the storm area. This resulted in these data sets making a large impact on the estimate of mass convergence and moisture fluxes, which were much smaller in the control runs. Overall this study points to the importance of high vertical resolution humidity data sets for improved model results. We note that the forecast impact from the moisture profiling data sets for some of the storms is even larger than the impact from the use of dropwindsonde based winds.

Ecological forecasts: An emerging imperative

Treesearch

James S. Clark; Steven R. Carpenter; Mary Barber; Scott Collins; Andy Dobson; Jonathan A. Foley; David M. Lodge; Mercedes Pascual; Roger Pielke; William Pizer; Cathy Pringle; Walter V. Reid; Kenneth A. Rose; Osvaldo Sala; William H. Schlesinger; Diana H. Wall; David Wear

2001-01-01

Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts...

Forecasts for NOAA Marine Sanctuaries

Science.gov Websites

/Forecast The Gray's Reef Sea Turtle Satellite Tagging Project utilizes satellite transmitter tags to Synopsis/Forecast(0-20nm) Synopsis/Forecast(20-60nm) The Gray's Reef Sea Turtle Satellite Tagging Project utilizes satellite transmitter tags to monitor adult and juvenile loggerhead sea click image for more

Effective detection of the tumors causing osteomalacia using [Tc-99m]-HYNIC-octreotide (99mTc-HYNIC-TOC) whole body scan.

PubMed

Jing, Hongli; Li, Fang; Zhuang, Hongming; Wang, Zhenghua; Tian, Jian; Xing, Xiaoping; Jin, Jin; Zhong, Dingrong; Zhang, Jingjing

2013-11-01

Tumor-induced osteomalacia (TIO) is an endocrine disorder caused by tumors producing excessive fibroblast growth factor-23 (FGF-23). The causative tumors are generally small, slow-growing benign mesenchymal tumors. The only cure of the disease depends on resection of the tumors, which are extremely difficult to localize due to their small sizes and rare locations. Since these tumors are known to express somatostatin receptors, this research was undertaken to evaluate efficacy of [Tc-99m]-HYNIC-octreotide (99mTc-HYNIC-TOC) whole body imaging in this clinical setting Images of 99mTc-HYNIC-TOC scans and clinical chart from 183 patients with hypophosphatemia and clinically suspected TIO were retrospectively reviewed. The scan findings were compared to the results of histopathological examinations and clinical follow-ups. Among 183 patients, 72 were confirmed to have TIO while 103 patients were found to have other causes of hypophosphatemia. The possibility of TIO could not be either diagnosed or excluded in the remaining 8 patients. For analytical purposes, these 8 patients who could neither be diagnosed nor excluded as having TIO were regarded as having the disease, bringing the total of TIO patients to 80. The 99mTc-HYNIC-TOC scan identified 69 tumors in 80 patients with TIO, which rendered a sensitivity of 86.3% (69/80). 99mTc-HYNIC-TOC scintigraphy excluded 102 patients without TIO with a specificity of 99.1% (102/103). The overall accuracy of 99mTc-HYNIC-TOC whole body scan in the localization of tumors responsible for osteomalacia is 93.4% (171/183). Whole body 99mTc-HYNIC-TOC imaging is effective in the localization of occult tumors causing TIO. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The impact bias in self and others: Affective and empathic forecasting in individuals with social anxiety.

PubMed

Arditte Hall, Kimberly A; Joormann, Jutta; Siemer, Matthias; Timpano, Kiara R

2018-07-01

People tend to overestimate the intensity and duration of affect (i.e., impact bias) when making predictions about their own and others' responding, termed affective and empathic forecasting, respectively. Research links impact biases to clinical symptoms of affective disorders, but little work has been done to examine how social anxiety is related to affective and empathic forecasting biases. The current investigation included two studies examining these associations in independent samples of young adults with dimensionally distributed social anxiety symptoms. Study 1 (N = 100) examined the associations between social anxiety and affective and empathic forecasts in response to a series of novel hypothetical vignettes in which a second-person narrator (i.e., the self) elicited anger, disgust, or happiness from another person (i.e., the other). Study 2 utilized an innovative experimental paradigm involving N = 68 participant dyads. Overall, results supported the existence of affective and empathic forecasting biases. Further, symptoms of social anxiety were associated with the tendency to overestimate one's own and others' negative affect and underestimate others' positive affect. Such forecasting biases may help to explain the avoidance that is characteristic of individuals with social anxiety and could represent a fruitful target of cognitive behavioral intervention. Copyright © 2018 Elsevier Ltd. All rights reserved.

Is a changing climate affecting the tropical cyclone behavior of Cape Verde?

NASA Astrophysics Data System (ADS)

Emmenegger, T. W.; Mann, M. E.; Evans, J. L.

2016-12-01

An existing dataset of synthetic tropical cyclone (TC) tracks derived from climate change simulations were used to explore TC variability within a 250 km radius of the Cape Verde Islands (16.5388N, 23.0418W). The synthetic sets were examined according to genesis point location, track projection, intensity, frequency, and seasonality within the observational era (1851 AD to present). These factors of TC variability have been shown to be strongly related to climate oscillations, thus the historical era was grouped by the increasing and decreasing regimes of sea surface temperature (SST) in the main development region (MDR) of the Atlantic Ocean. Numerous studies have examined Atlantic Basin activity throughout this era; the goal of this study is to investigate possible variations in TC behavior around Cape Verde, ultimately determining whether Cape Verde experiences similar fluctuations in activity as observed basin-wide. We find that several facets of TC variability such as intensity, seasonality, and genesis point location around Cape Verde are not significantly different to that of the entire basin, thus forecasts of the entire basin in these respects may also apply to our site. A long-term trend of increasing TC frequency can be identified basin-wide within the observed set, yet activity around Cape Verde does not display this same behavior observably or in any synthetic set. A relationship between the location of genesis points and the regimes of SST fluctuation is shown to be existent. We find both more observed and synthetic genesis points within the vicinity of Cape Verde during cool periods, and an eastward and equatorward shift in cyclogenesis is evident during warm regimes. This southeastern shift in genesis points attributes to the increased intensities of TCs seen during periods of warmer SST. Years of increased SST are additionally linked to an earlier seasonality in Cape Verde.

Role of CD8 Regulatory T Cells versus Tc1 and Tc17 Cells in the Development of Human Graft-versus-Host Disease.

PubMed

Gutiérrez-Hoya, Adriana; López-Santiago, Rubén; Vela-Ojeda, Jorge; Montiel-Cervantes, Laura; Rodríguez-Cortés, Octavio; Rosales-García, Víctor; Paredes-Cervantes, Vladimir; Flores-Mejía, Raúl; Sandoval-Borrego, Daniela; Moreno-Lafont, Martha

2017-01-01

CD8 + T cells that secrete proinflammatory cytokines play a central role in exacerbation of inflammation; however, a new subpopulation of CD8 regulatory T cells has recently been characterized. This study analyzes the prominent role of these different subpopulations in the development of graft-versus-host disease (GVHD). Samples from 8 healthy donors mobilized with Filgrastim® (G-CSF) and 18 patients who underwent allogeneic hematopoietic stem cell transplantation (HSCT) were evaluated by flow cytometry. Mobilization induced an increase in Tc1 ( p < 0.01), Th1 ( p < 0.001), Tc17 ( p < 0.05), and CD8 + IL-10 + cells ( p < 0.05), showing that G-CSF induces both pro- and anti-inflammatory profiles. Donor-patient correlation revealed a trend ( p = 0.06) toward the development of GVHD in patients who receive a high percentage of Tc1 cells. Patients with acute GVHD (aGVHD), either active or controlled, and patients without GVHD were evaluated; patients with active aGVHD had a higher percentage of Tc1 ( p < 0.01) and Tc17 ( p < 0.05) cells, as opposed to patients without GVHD in whom a higher percentage of CD8 Treg cells ( p < 0.01) was found. These findings indicate that the increase in Tc1 and Tc17 cells is associated with GVHD development, while regulatory CD8 T cells might have a protective role in this disease. These tests can be used to monitor and control GVHD.

Role of CD8 Regulatory T Cells versus Tc1 and Tc17 Cells in the Development of Human Graft-versus-Host Disease

PubMed Central

Gutiérrez-Hoya, Adriana; López-Santiago, Rubén; Vela-Ojeda, Jorge; Montiel-Cervantes, Laura; Rodríguez-Cortés, Octavio; Rosales-García, Víctor; Flores-Mejía, Raúl; Sandoval-Borrego, Daniela

2017-01-01

CD8+ T cells that secrete proinflammatory cytokines play a central role in exacerbation of inflammation; however, a new subpopulation of CD8 regulatory T cells has recently been characterized. This study analyzes the prominent role of these different subpopulations in the development of graft-versus-host disease (GVHD). Samples from 8 healthy donors mobilized with Filgrastim® (G-CSF) and 18 patients who underwent allogeneic hematopoietic stem cell transplantation (HSCT) were evaluated by flow cytometry. Mobilization induced an increase in Tc1 (p < 0.01), Th1 (p < 0.001), Tc17 (p < 0.05), and CD8+IL-10+ cells (p < 0.05), showing that G-CSF induces both pro- and anti-inflammatory profiles. Donor-patient correlation revealed a trend (p = 0.06) toward the development of GVHD in patients who receive a high percentage of Tc1 cells. Patients with acute GVHD (aGVHD), either active or controlled, and patients without GVHD were evaluated; patients with active aGVHD had a higher percentage of Tc1 (p < 0.01) and Tc17 (p < 0.05) cells, as opposed to patients without GVHD in whom a higher percentage of CD8 Treg cells (p < 0.01) was found. These findings indicate that the increase in Tc1 and Tc17 cells is associated with GVHD development, while regulatory CD8 T cells might have a protective role in this disease. These tests can be used to monitor and control GVHD. PMID:28164135

Next-Day Earthquake Forecasts for California

NASA Astrophysics Data System (ADS)

Werner, M. J.; Jackson, D. D.; Kagan, Y. Y.

2008-12-01

We implemented a daily forecast of m > 4 earthquakes for California in the format suitable for testing in community-based earthquake predictability experiments: Regional Earthquake Likelihood Models (RELM) and the Collaboratory for the Study of Earthquake Predictability (CSEP). The forecast is based on near-real time earthquake reports from the ANSS catalog above magnitude 2 and will be available online. The model used to generate the forecasts is based on the Epidemic-Type Earthquake Sequence (ETES) model, a stochastic model of clustered and triggered seismicity. Our particular implementation is based on the earlier work of Helmstetter et al. (2006, 2007), but we extended the forecast to all of Cali-fornia, use more data to calibrate the model and its parameters, and made some modifications. Our forecasts will compete against the Short-Term Earthquake Probabilities (STEP) forecasts of Gersten-berger et al. (2005) and other models in the next-day testing class of the CSEP experiment in California. We illustrate our forecasts with examples and discuss preliminary results.

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

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

Real-time eruption forecasting using the material Failure Forecast Method with a Bayesian approach

NASA Astrophysics Data System (ADS)

Boué, A.; Lesage, P.; Cortés, G.; Valette, B.; Reyes-Dávila, G.

2015-04-01

Many attempts for deterministic forecasting of eruptions and landslides have been performed using the material Failure Forecast Method (FFM). This method consists in adjusting an empirical power law on precursory patterns of seismicity or deformation. Until now, most of the studies have presented hindsight forecasts based on complete time series of precursors and do not evaluate the ability of the method for carrying out real-time forecasting with partial precursory sequences. In this study, we present a rigorous approach of the FFM designed for real-time applications on volcano-seismic precursors. We use a Bayesian approach based on the FFM theory and an automatic classification of seismic events. The probability distributions of the data deduced from the performance of this classification are used as input. As output, it provides the probability of the forecast time at each observation time before the eruption. The spread of the a posteriori probability density function of the prediction time and its stability with respect to the observation time are used as criteria to evaluate the reliability of the forecast. We test the method on precursory accelerations of long-period seismicity prior to vulcanian explosions at Volcán de Colima (Mexico). For explosions preceded by a single phase of seismic acceleration, we obtain accurate and reliable forecasts using approximately 80% of the whole precursory sequence. It is, however, more difficult to apply the method to multiple acceleration patterns.

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.

Traffic forecasting report : 2007.

DOT National Transportation Integrated Search

2008-05-01

This is the sixth edition of the Traffic Forecasting Report (TFR). This edition of the TFR contains the latest (predominantly 2007) forecasting/modeling data as follows: : Functional class average traffic volume growth rates and trends : Vehi...

Operational Hydrological Forecasting During the Iphex-iop Campaign - Meet the Challenge

NASA Technical Reports Server (NTRS)

Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa D.; Barros, Ana P.

2016-01-01

An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts

Operational hydrological forecasting during the IPHEx-IOP campaign - Meet the challenge

NASA Astrophysics Data System (ADS)

Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa; Barros, Ana P.

2016-10-01

An operational streamflow forecasting testbed was implemented during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP) in May-June 2014 to characterize flood predictability in complex terrain. Specifically, hydrological forecasts were issued daily for 12 headwater catchments in the Southern Appalachians using the Duke Coupled surface-groundwater Hydrology Model (DCHM) forced by hourly atmospheric fields and QPFs (Quantitative Precipitation Forecasts) produced by the NASA-Unified Weather Research and Forecasting (NU-WRF) model. Previous day hindcasts forced by radar-based QPEs (Quantitative Precipitation Estimates) were used to provide initial conditions for present day forecasts. This manuscript first describes the operational testbed framework and workflow during the IPHEx-IOP including a synthesis of results. Second, various data assimilation approaches are explored a posteriori (post-IOP) to improve operational (flash) flood forecasting. Although all flood events during the IOP were predicted by the IPHEx operational testbed with lead times of up to 6 h, significant errors of over- and, or under-prediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. To improve operational flood prediction, three data-merging strategies were pursued post-IOP: (1) the spatial patterns of QPFs were improved through assimilation of satellite-based microwave radiances into NU-WRF; (2) QPEs were improved by merging raingauge observations with ground-based radar observations using bias-correction methods to produce streamflow hindcasts and associated uncertainty envelope capturing the streamflow observations, and (3) river discharge observations were assimilated into the DCHM to improve streamflow forecasts using the Ensemble Kalman Filter (EnKF), the fixed-lag Ensemble Kalman Smoother (EnKS), and the Asynchronous EnKF (i.e. AEnKF) methods. Both flood hindcasts and forecasts

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

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 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

Using Seasonal Forecasts for medium-term Electricity Demand Forecasting on Italy

NASA Astrophysics Data System (ADS)

De Felice, M.; Alessandri, A.; Ruti, P.

2012-12-01

Electricity demand forecast is an essential tool for energy management and operation scheduling for electric utilities. In power engineering, medium-term forecasting is defined as the prediction up to 12 months ahead, and commonly is performed considering weather climatology and not actual forecasts. This work aims to analyze the predictability of electricity demand on seasonal time scale, considering seasonal samples, i.e. average on three months. Electricity demand data has been provided by Italian Transmission System Operator for eight different geographical areas, in Fig. 1 for each area is shown the average yearly demand anomaly for each season. This work uses data for each summer during 1990-2010 and all the datasets have been pre-processed to remove trends and reduce the influence of calendar and economic effects. The choice of focusing this research on the summer period is due to the critical peaks of demand that power grid is subject during hot days. Weather data have been included considering observations provided by ECMWF ERA-INTERIM reanalyses. Primitive variables (2-metres temperature, pressure, etc) and derived variables (cooling and heating degree days) have been averaged for summer months. A particular attention has been given to the influence of persistence of positive temperature anomaly and a derived variable which count the number of consecutive days of extreme-days has been used. Electricity demand forecast has been performed using linear and nonlinear regression methods and stepwise model selection procedures have been used to perform a variable selection with respect to performance measures. Significance tests on multiple linear regression showed the importance of cooling degree days during summer in the North-East and South of Italy with an increase of statistical significance after 2003, a result consistent with the diffusion of air condition and ventilation equipment in the last decade. Finally, using seasonal climate forecasts we evaluate

The impact trajectory of asteroid 2008 TC3

NASA Astrophysics Data System (ADS)

Farnocchia, Davide; Jenniskens, Peter; Robertson, Darrel K.; Chesley, Steven R.; Dimare, Linda; Chodas, Paul W.

2017-09-01

The impact of asteroid 2008 TC3 was an unprecedented event-the first ever predicted impact of a near-Earth object. When it was first detected about 20 h before impact, 2008 TC3 was still farther away than the Moon. Once it was recognized as an impactor and announced as such, 2008 TC3 began to receive considerable attention from astronomical observers. Using the unprecedented dataset of nearly 900 astrometric observations and the latest observation debiasing and weighting techniques, we estimate the precise trajectory of 2008 TC3 and its impact ground track. At the entry point into the atmosphere, the 3-σ formal uncertainty in predicted position is an ellipse only 1.4 km × 0.15 km in size. The locations of the many meteorites recovered from the desert floor mark the asteroid's actual ground track and provide a unique opportunity to validate trajectory models. We find that the second-order zonal harmonics of the Earth gravity field moves the ground track by more than 1 km and the location along the ground track by more than 2 km, while non-zonal and higher order harmonics change the impact prediction by less than 20 m. The contribution of atmospheric drag to the trajectory of 2008 TC3 is similar to the numerical integration error level, a few meters, down to an altitude of 50 km. Integrating forward to lower altitudes and ignoring the break-up of 2008 TC3, atmospheric drag causes an along-track deviation that can be as large as a few kilometers at sea level.

Unified electronic phase diagram for hole-doped high- Tc cuprates

NASA Astrophysics Data System (ADS)

Honma, T.; Hor, P. H.

2008-05-01

We have analyzed various characteristic temperatures and energies of hole-doped high- Tc cuprates as a function of a dimensionless hole-doping concentration (pu) . Entirely based on the experimental grounds, we construct a unified electronic phase diagram (UEPD), where three characteristic temperatures ( T∗ ’s) and their corresponding energies ( E∗ ’s) converge as pu increases in the underdoped regime. T∗ ’s and E∗ ’s merge together with the Tc curve and 3.5kBTc curve at pu˜1.1 in the overdoped regime, respectively. They finally go to zero at pu˜1.3 . The UEPD follows an asymmetric half-dome-shaped Tc curve, in which Tc appears at pu˜0.4 , reaches a maximum at pu˜1 , and rapidly goes to zero at pu˜1.3 . The asymmetric half-dome-shaped Tc curve is at odds with the well-known symmetric superconducting dome for La2-xSrxCuO4 (SrD-La214), in which two characteristic temperatures and energies converge as pu increases and merge together at pu˜1.6 , where Tc goes to zero. The UEPD clearly shows that pseudogap phase precedes and coexists with high temperature superconductivity in the underdoped and overdoped regimes, respectively. It is also clearly seen that the upper limit of high- Tc cuprate physics ends at a hole concentration that equals to 1.3 times the optimal doping concentration for almost all high- Tc cuprate materials and 1.6 times the optimal doping concentration for the SrD-La214. Our analysis strongly suggests that pseudogap is a precursor of high- Tc superconductivity, the observed quantum critical point inside the superconducting dome may be related to the end point of UEPD, and the normal state of the underdoped and overdoped high temperature superconductors cannot be regarded as a conventional Fermi liquid phase.

Evaluating sub-seasonal skill in probabilistic forecasts of Atmospheric Rivers and associated extreme events

NASA Astrophysics Data System (ADS)

Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.

The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States

PubMed Central

Prestemon, Jeffrey P.; Butry, David T.; Thomas, Douglas S.

2017-01-01

Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires. PMID:28769549

The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States.

PubMed

Prestemon, Jeffrey P; Butry, David T; Thomas, Douglas S

2016-01-01

Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires.

Computers and Technological Forecasting