Reply on RC2

Numerical models of atmospheric dispersion are used for predicting the health and environmental consequences of nuclear accidents, in order to anticipate the countermeasures necessary to protect the populations. However, the simulations of these models suffer from significant uncertainties, arising in particular from input data: weather conditions and source term. To characterize weather uncertainties, it is essential to combine a well-known source term data and meteorological ensembles to generate ensemble dispersion simulations which has the potential to produce different possible scenarios of radionuclides dispersion during emergency situations. In this study, the fine-scale operational weather ensemble AROME-EPS from Météo-France is coupled to the Gaussian puff model pX developed by French Institute for Radiation Protection and Nuclear Safety (IRSN). The source term data is provided by Orano La Hague reprocessing plant (RP) that regularly discharges 85Kr during the spent nuclear fuel reprocessing process. Then, to evaluate the dispersion results, a continuous measurement campaign of 85Kr air concentration was recently conducted by the Laboratory of Radioecology in Cherbourg (LRC) of IRSN, around RP in the North-Cotentin peninsula. This paper presents a probabilistic approach to study the meteorological uncertainties in dispersion simulations at local and medium distances (2–20 km). As first step, the quality of AROME-EPS forecasts is confirmed by comparison with observations from both Météo-France and IRSN. The following step is to assess the probabilistic performance of the dispersion ensemble simulation, as well as the sensitivity of dispersion results to the method used to calculate atmospheric stability fields and their associated dispersion Gaussian standard deviations. Two probabilistic scores are used: Relative Operating Characteristic (ROC) curves and Peirce Skill Score (PSS). The results show that the stability diagnostics of Pasquill provides better dispersion simulations. In addition, the ensemble dispersion performs better than deterministic one, and the optimum decision threshold (PSS maximum) is 3 members. These results highlight the added value of ensemble forecasts compared to a single deterministic one, and their potential interest in the decision process during crisis situations.

Abstract. Numerical atmospheric dispersion models (ADMs) are used for predicting the health and environmental consequences of nuclear accidents in order to anticipate countermeasures necessary to protect the populations. However, these simulations suffer from significant uncertainties, arising in particular from input data: weather conditions and source term. Meteorological ensembles are already used operationally to characterize uncertainties in weather predictions. Combined with dispersion models, these ensembles produce different scenarios of radionuclide dispersion, called “members”, representative of the variety of possible forecasts. In this study, the fine-scale operational weather ensemble AROME-EPS (Applications of Research to Operations at Mesoscale-Ensemble Prediction System) from Météo-France is coupled with the Gaussian puff model pX developed by the IRSN (French Institute for Radiation Protection and Nuclear Safety). The source term data are provided at 10 min resolution by the Orano La Hague reprocessing plant (RP) that regularly discharges 85Kr during the spent nuclear fuel reprocessing process. In addition, a continuous measurement campaign of 85Kr air concentration was recently conducted by the Laboratory of Radioecology in Cherbourg (LRC) of the IRSN, within 20 km of the RP in the North-Cotentin peninsula, and is used for model evaluation. This paper presents a probabilistic approach to study the meteorological uncertainties in dispersion simulations at local and medium distances (2–20 km). First, the quality of AROME-EPS forecasts is confirmed by comparison with observations from both Météo-France and the IRSN. Then, the probabilistic performance of the atmospheric dispersion simulations was evaluated by comparison to the 85Kr measurements carried out during a period of 2 months, using two probabilistic scores: relative operating characteristic (ROC) curves and Peirce skill score (PSS). The sensitivity of dispersion results to the method used for the calculation of atmospheric stability and associated Gaussian dispersion standard deviations is also discussed. A desirable feature for a model used in emergency response is the ability to correctly predict exceedance of a given value (for instance, a dose guide level). When using an ensemble of simulations, the “decision threshold” is the number of members predicting an event above which this event should be considered probable. In the case of the 16-member dispersion ensemble used here, the optimal decision threshold was found to be 3 members, above which the ensemble better predicts the observed peaks than the deterministic simulation. These results highlight the added value of ensemble forecasts compared to a single deterministic one and their potential interest in the decision process during crisis situations.

The value of a diagnostic test depends on most cases on its ability to discriminate between patients with and without a certain disease. One way of evaluating a diagnostic test is to use the relative operating characteristic curve (ROC curve) and the differential positive rate (DPR). The ROC curve displays the relationship between the true positive ratio and the false positive ratio for a range of cutoff values and it can be used to compare various diagnostic tests under equivalent conditions (equal true positive ratios or false positive ratios) and over the entire range of cutoff values. The DPR is the difference between the true positive ratio and the false positive ratio at various cutoff values and it can be used to obtain the cutoff value associated with the highest sensitivity and specificity. The purpose of this study was to describe the evaluation and comparison of diagnostic tests using ROC curves and DPR. Eventually, the positive and negative predictive values were used to assess the differences between the sensitivity and specificity obtained when the upper limit of the reference interval, or the optimal cutoff value indicated by the DPR, was used as cutoff value. To illustrate the methods, the 2 h post-prandial total serum bile acid concentration (PSBA) and the alanine aminotransferase activity (ALAT) in the diagnosis of primary or secondary hepatobiliary diseases in dogs were used. The ROC curves showed, as expected from previous studies, that PSBA was superior to ALAT in diagnosing dogs with hepatobiliary diseases. Using DPR, the optimal cutoff value for PSBA was suggested to be 15.48 mumol/l. Compared to the traditionally used cutoff value of 22.24 mumol/l, no decisive difference in the positive predictive values were observed. However, the cutoff value of 15.48 mumol/l appeared to produce higher negative predictive values compared to a cutoff value of 22.24 mumol/l. Seemingly, ROC curves and DPR are simple methods useful to the evaluation of diagnostic tests and due to the simplicity, there seems to be a great potential for these methods in the evaluation of diagnostic tests in veterinary medicine.

Given increasing computing power, an important question is whether additional computational resources would be better spent reducing the horizontal grid spacing of a convection-allowing model (CAM) or adding members to form CAM ensembles. The present study investigates this question as it applies to CAM-derived next-day probabilistic severe weather forecasts created by using forecast updraft helicity as a severe weather proxy for 63 days of the 2010 and 2011 NOAA Hazardous Weather Testbed Spring Forecasting Experiments. Forecasts derived from three sets of Weather Research and Forecasting Model configurations are tested: a 1-km deterministic model, a 4-km deterministic model, and an 11-member, 4-km ensemble. Forecast quality is evaluated using relative operating characteristic (ROC) curves, attributes diagrams, and performance diagrams, and forecasts from five representative cases are analyzed to investigate their relative quality and value in a variety of situations. While no statistically significant differences exist between the 4- and 1-km deterministic forecasts in terms of area under ROC curves, the 4-km ensemble forecasts offer weakly significant improvements over the 4-km deterministic forecasts over the entire 63-day dataset. Further, the 4-km ensemble forecasts generally provide greater forecast quality relative to either of the deterministic forecasts on an individual day. Collectively, these results suggest that, for purposes of improving next-day CAM-derived probabilistic severe weather forecasts, additional computing resources may be better spent on adding members to form CAM ensembles than on reducing the horizontal grid spacing of a deterministic model below 4 km.

An approach to evaluating probability forecasts for dichotomous events, based on their economic value over all possible cost/loss ratio decision problems, is proposed. The resulting Value Score (VS) curve shows non‐dimensionalised relative economic value as a function of the cost/loss ratios for different decision‐makers, over their full meaningful range. The VS curve is similar in terms of computational mechanics and graphical display to the Relative Operating Characteristic (ROC) curve, but the ROC curve is shown to be insensitive to either conditional or unconditional biases and thus to reflect potential rather than actual skill. The possibility of collapsing the VS curve into a single scalar score is addressed, and it is shown that the results can depend very strongly on the assumed distribution of cost/loss ratios in the community of forecast users. Copyright © 2001 Royal Meteorological Society

Serum progesterone predicts abnormal gestations in clomiphene citrate conception cycles as well as in spontaneous conception cycles

The General Health Questionnaire (GHQ-12) (Goldberg, 1972) and the Self Report Questionnaire (SRQ-20) (Harding et al. 1980) were simultaneously validated against the criterion of the Clinical Interview Schedule (CIS) (Goldberg et al. 1970) in three primary care clinics in the city of Sao Paulo, Brazil. A comparison between the two screening instruments was carried out. The product-moment correlation between the two sets of scores was +0.72, and the validation coefficients for the GHQ-12 and the SRQ-20 were respectively: sensitivity 85% and 83%; specificity 79% and 80%; overall misclassification rate 18% and 19%. The two screening instruments were further compared by the application of Relative Operating Characteristic (ROC) analysis and, again, were found to be very similar in performance. The area under the ROC curve was 0.87 for the GHQ and 0.90 for the SRQ-20 (Z = 0.92, NS). Both psychiatric screening instruments were therefore found to be acceptably valid when assessed against the CIS in three primary care settings in Brazil. The application of ROC analysis to studies of this kind was feasible and straightforward. It was found to be superior to the conventional method of presentation of validity data. It is recommended that the application of ROC analysis to psychiatric screening studies be further utilized and explored.

In medical usage, relative operating characteristics (ROC) refer to the symptoms, signs, and laboratory values used for making a diagnosis. Diagnosis analysis by ROC measures diagnosis performance independently of the diagnostic criteria used, thus revealing the arbitrary character of diagnosis. In order to carry out ROC analysis, the diagnosis has to be graded in levels of certainty of the presence of disease (or suspicion of a lesion). When both the graded diagnosis decisions and the ultimate proof of presence or absence of disease are available, ROC analysis can easily be carried out. Analysis of 50,102 successive examinations of 19,400 women in the Utrecht breast cancer screening projects presents a remarkably good fit of the observed data with the calculated values. In the medical context even small deviations of the actual sensitivity and specificity values from the ROC curve values must be considered as signs of differences in the diagnosis procedure and should lead to further analysis of the diagnostic criteria and the examined population. Consequently the separate effect of diagnosis impairment by the mammographic risk patterns (Wolfe) on diagnostic accuracy could be isolated. The effect of age on the detection capability of breast cancer by mammography appeared to operate in narrow age groups.

In the article the problem of the system of urban management in emergency and crisis situations were considered. Composition and functions of the municipal government have been characterized. It was disclosed the concept of "emergency" and "crisis". Typology of crisis and emergency situations include: natural disasters, manmade disasters, sanitary-epidemiological, socio-political and economic crises. Crises have been classified: the reasons of occurrence, in the sphere of manifestation, on the possibilities of forecasting and duration. Typical measures to manage the liquidation of emergency situations in the city have been identified. Principles and steps of the City of crisis management are presented. Analysis was performed operational management experience life support in an emergency situation caused by the fighting. Was justified by the implementation of additional features for managing urban emergency response and overcome the consequences of the social, economic and environmental crisis. Perform additional functions involves restoration of vital facilities of the city, which are damaged by the fighting. Additional features of urban governance provide fault detection of communal, social, engineering, road infrastructure. Function provides an assessment permanently damaged facilities. Function ensures the development of the investment project for restoration of urban infrastructure. Analysis functions provide resource support the restoration project. Functions provide monitoring restoration projects of urban infrastructure.

The operational limited‐area model, HIRLAM, at the Norwegian Meteorological Institute is used at 0.25° latitude/longitude resolution for ensemble weather prediction over Northern Europe and adjacent parts of the North Atlantic Ocean; this system is called LAMEPS. Initial and lateral boundary perturbations are taken from coarse‐resolution European Centre for Medium‐Range Weather Forecasts global ensemble members based on targeted singular vectors (TEPS). Five winter and five summer cases in 1997 consisting of 20 ensemble members plus one control forecast are integrated. Two sets of ensembles are generated, one for which both initial and lateral boundary conditions are perturbed, and another with only the initial fields perturbed. The LAMEPS results are compared to those of TEPS using the following measures: r.m.s. ensemble spread of 500 hPa geopotential height; r.m.s. ensemble spread of mean‐sea‐level pressure; Brier Skill Scores (BSS); Relative Operating Characteristic (ROC) curves; and cost/loss analyses. For forecasts longer than 12 hours, all measures show that perturbing the boundary fields is crucial for the performance of LAMEPS. For the winter cases TEPS has slightly larger ensemble spread than LAMEPS, but this is reversed for the summer cases. Results from BSS, ROC and cost/loss analyses show that LAMEPS performed considerably better than TEPS for precipitation, a result that is promising for forecasting extreme precipitation amounts. We believe this result to be linked to the high predictability of mesoscale flows controlled by complex topography. For two‐metre temperature, however, TEPS frequently performed better than LAMEPS. Copyright © 2002 Royal Meteorological Society

Landslide susceptibility assessment forms the basis of any hazard mapping, which is one of the essential parts of quantitative risk mapping. For the same study area, different susceptibility maps can be achieved depending on the type of susceptibility mapping methods, mapping unit, and scale. Although there are various methods of obtaining susceptibility maps, the efficiency and performance of each method should be evaluated. In this study the effect of mapping unit and susceptibility mapping method on landslide susceptibility assessment is investigated. When analyzing the effect of susceptibility mapping method, logistic regression (LR) which is widely used in landslide susceptibility mapping and, spatial regression (SR), which have not been used for landslide susceptibility mapping, are selected. The susceptibility maps with logistic and spatial regression models are obtained using two different mapping units namely slope unit-based and grid-based mapping units. The procedure for investigation of effect of mapping unit on different susceptibility mapping methods is applied to Kumluca watershed, in Bartin Province of Western Black Sea Region, Turkey. 18 factor maps are prepared for landslide susceptibility assessment in the study region. Geographic information systems and remote sensing techniques are used to create the landslide factor maps, to obtain susceptibility maps and to compare the results. The relative operating characteristics (ROC) curve is used to compare the predictive abilities of each model and mapping unit and also the accuracy is evaluated depending on the observations made during field surveys. By analyzing the area under the ROC curve for grid-based and slope unit-based mapping units, it can be concluded that SR model provide better predictive performance (0.774 in grids and 0.898 in slope units) as compared to the LR model (0.744 in grids and 0.820 in slope units). This result is also supported by the accuracy analysis. For both mapping units, the SR model provides more accurate result (0.55 for grids and 0.57 for slope units) than the LR model (0.50 for grids and 0.48 for slopes). The main reason for this better performance is that the spatial correlations between the mapping units are incorporated into the model in SR while this fact is not considered in LR model.

The prognosis of patients with advanced hepatocellular carcinoma (HCC) is poor and testing drug efficacy in clinical trials is hazardous. This study was aimed to evaluate different prognostic scoring systems for HCC in estimating prognosis (3-month survival and overall survival (OS)). From November 2008 to April 2010, 208 patients with advanced HCC who were not amendable to locoregional therapy were included in this study. Data were collected to classify patients according to the following: the Japanese integrated staging scoring system, TNM stage by the Liver Cancer Study Group of Japan criteria, TNM 6th edn, the cancer of the liver Italian program scoring system (CLIP), the advanced liver cancer prognostic system (ALCPS), the model of end-stage liver disease, the Groupe d'étude et de Traitement du Carcinome Hepatocellulaire (GETCH) scoring system, the Chinese University prognostic index staging system (CUPI), the Okuda scoring system, the Child-Pugh score, the Tokyo scoring system and the Barcelona Clinic liver cancer staging. Survival analysis and relative operating characteristic (ROC) were utilized to access the prognostic value of each scoring system. ALCPS performed best, with the largest area under the ROC curve in predicting 3-month OS (sensitivity 76.32%, specificity 78.72%). CLIP and CUPI were similar to ALCPS in prognostic discrimination but with relatively lower power. ALCPS, CLIP and CUPI are the preferred scoring systems in the prediction of OS and 3-month survival among the 12 systems analyzed, and should be used as inclusion criteria in clinical trials for advanced HCC patients.

Providing useful inflow forecasts of the Manantali dam is critical for zonal consumption and agricultural water supply, power production, flood and drought control and management (Shin et al., Meteorol Appl 27:e1827, 2019). Probabilistic approaches through ensemble forecasting systems are often used to provide more rational and useful hydrological information. This paper aims at implementing an ensemble forecasting system at the Senegal River upper the Manantali dam. Rainfall ensemble is obtained through harmonic analysis and an ARIMA stochastic process. Cyclical errors that are within rainfall cyclical behavior from the stochastic modeling are settled and processed using multivariate statistic tools to dress a rainfall ensemble forecast. The rainfall ensemble is used as input to run the HBV-light to product streamflow ensemble forecasts. A number of 61 forecasted rainfall time series are then used to run already calibrated hydrological model to produce hydrological ensemble forecasts called raw ensemble. In addition, the affine kernel dressing method is applied to the raw ensemble to obtain another ensemble. Both ensembles are evaluated using on the one hand deterministic verifications such the linear correlation, the mean error, the mean absolute error and the root-mean-squared error, and on the other hand, probabilistic scores (Brier score, rank probability score and continuous rank probability score) and diagrams (attribute diagram and relative operating characteristics curve). Results are satisfactory as at deterministic than probabilistic scale, particularly considering reliability, resolution and skill of the systems. For both ensembles, correlation between the averages of the members and corresponding observations is about 0.871. In addition, the dressing method globally improved the performances of ensemble forecasting system. Thus, both schemes system can help decision maker of the Manantali dam in water resources management.

Monitoring land cover over large areas on a yearly basis is challenging. The spatial and temporal consistency of an object-based change detection algorithm was tested through a multi-year application on the forest of Borneo, using SPOT-VEGETATION time series from 2000 to 2008. Continuous change thresholds allowed the tuning of the algorithm according to specific requirements in terms of omission and commission errors. The accuracy of the method was assessed using the ROC (relative operating characteristics) curves, which were found useful to evaluate the performance of the method independently of the selected threshold and to support the selection of an optimal threshold. The forest area that annually changed between 2000 and 2008 was detected and a cumulative change map was produced. The resulting change rates and the distribution of the forest change patterns were in agreement with other sources of information. These results demonstrated the very promising temporal consistency of the proposed approach. Further work aims at testing it at larger scales.

A pipe inspection round robin entitled Mini-Round Robin'' was conducted at Pacific Northwest Laboratory from May 1985 through October 1985. The research was sponsored by the US Nuclear Regulatory Commission, Office of Nuclear Regulatory Research under a program entitled Evaluation and Improvement of NDE Reliability for Inservice Inspection of Light Water Reactors.'' The Mini-Round Robin (MRR) measured the intergranular stress corrosion (GSC) crack detection and sizing capabilities of inservice inspection (ISI) inspectors that had passed the requirements of IEB 83-02 and the Electric Power Research Institute (EPRI) sizing training course. The MRR data base was compared with an earlier Pipe Inspection Round Robin (PIRR) that had measured the performance of inservice inspection prior to 1982. Comparison of the MRR and PIRR data bases indicates no significant change in the inspection capability for detecting IGSCC. Also, when comparing detection of long and short cracks, no difference in detection capability was measured. An improvement in the ability to differentiate between shallow and deeper IGSCC was found when the MRR sizing capability was compared with an earlier sizing round robin conducted by the EPRI. In addition to the pipe inspection round robin, a human factors study was conducted in conjunction with the Mini-Round Robin. The most important result of the human factors study is that the Relative Operating Characteristics (ROC) curves provide a better methodology for describing inspector performance than only probability of detection (POD) or single-point crack/no crack data. 6 refs., 55 figs., 18 tabs.