scholarly journals Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

2021 ◽  
Author(s):  
Chloé Radice ◽  
Hélène Brogniez ◽  
Pierre-Emmanuel Kirstetter ◽  
Philippe Chambon
Keyword(s):  
Relative Humidity ◽  
Weather Forecasting ◽  
Atmospheric Model ◽  
Individual Case ◽  
Forecasting Model ◽  
Spatial And Temporal Variability ◽  
Reference Distribution ◽  
Numerical Weather Forecasting ◽  
Novel Method ◽  
The Individual

Abstract. A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Météo-France numerical weather forecasting model ARPEGE using probability density functions (PDF) of RH estimated from the SAPHIR microwave sounder. The satellite RH reference is derived by aggregating footprint-scale probabilistic RH to match the spatial and temporal resolution of ARPEGE over the April-May-June 2018 period. The probabilistic comparison is discussed with respect to a classical deterministic comparison confronting each model RH value to the reference average and using a set confidence interval. The study first documents the significant spatial and temporal variability of the reference distribution spread and shape. It warrants the need for a finer assessment at the individual case level to characterise specific situations beyond the classical bulk comparison using determinist “best” reference estimates. The probabilistic comparison allows for a more contrasted assessment than the deterministic one. Specifically, it reveals cases where the ARPEGE simulated values falling within the deterministic confidence range actually correspond to extreme departures in the reference distribution.

scholarly journals A snowmelt runoff forecasting model coupling WRF and DHSVM

2009 ◽  
Vol 13 (10) ◽  
pp. 1897-1906 ◽  
Author(s):  
Q. Zhao ◽  
Z. Liu ◽  
B. Ye ◽  
Y. Qin ◽  
Z. Wei ◽  
...  
Keyword(s):  
Weather Forecasting ◽  
Atmospheric Model ◽  
Forecasting Model ◽  
Tianshan Mountain ◽  
Mountain Range ◽  
Snowmelt Runoff ◽  
Runoff Simulation ◽  
Limited Region ◽  
Runoff Forecasting ◽  
Forecasting System

Abstract. This study linked the Weather Research and Forecasting (WRF) modelling system and the Distributed Hydrology Soil Vegetation Model (DHSVM) to forecast snowmelt runoff. The study area was the 800 km2 Juntanghu watershed of the northern slopes of Tianshan Mountain Range. This paper investigated snowmelt runoff forecasting models suitable for meso-microscale application. In this study, a limited-region 24-h Numeric Weather Forecasting System was formulated using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. Using the WRF forecasts, the DHSVM hydrological model was used to predict 24 h snowmelt runoff at the outlet of the Juntanghu watershed. Forecasted results showed a good similarity to the observed data, and the average relative error of maximum runoff simulation was less than 15%. The results demonstrate the potential of using a meso-microscale snowmelt runoff forecasting model for forecasting floods. The model provides a longer forecast period compared with traditional models such as those based on rain gauges or statistical forecasting.

scholarly journals The snowmelt runoff forecasting model of coupling WRF and DHSVM

2009 ◽  
Vol 6 (2) ◽  
pp. 3335-3357 ◽  
Author(s):  
Q. Zhao ◽  
Z. Liu ◽  
M. Li ◽  
Z. Wei ◽  
S. Fang
Keyword(s):  
Weather Forecasting ◽  
Atmospheric Model ◽  
Forecasting Model ◽  
Snowmelt Runoff ◽  
Runoff Simulation ◽  
Limited Region ◽  
Model Driven ◽  
Absolute Relative Error ◽  
Runoff Forecasting ◽  
Average Absolute Relative Error

Abstract. This study used the Weather Research and Forecasting (WRF) modeling system and the Distributed Hydrology-Soil-Vegetation Model (DHSVM) to forecast the snowmelt runoff in the 800 km2 Juntanghu watershed of the northern slope of Tianshan Mountains from 29 February–6 March 2008. This paper made an exploration for snowmelt runoff forecasting model combing closely practical application in meso-microscale. It included: (1) A limited-region 24-h Numeric Weather Forecasting System was established by using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. (2) The DHSVM hydrological model driven by WRF forecasts was used to predicate 24 h snowmelt runoff at the outlet of Juntanghu watershed. The forecasted result shows a good agreement with the observed data, and the average absolute relative error of maximum runoff simulation result is less than 15%. The result demonstrates the potential of using meso-microscale snowmelt runoff forecasting model for flood forecast. The model can provide a longer forecast period compared to traditional models such as those based on rain gauges, statistical forecast.

Shoulder Pain at Work: Causation Analysis

2017 ◽  
Vol 22 (1) ◽  
pp. 11-16
Author(s):  
Joel Weddington ◽  
Charles N. Brooks ◽  
Mark Melhorn ◽  
Christopher R. Brigham
Keyword(s):  
Epidemiological Data ◽  
Case Law ◽  
Individual Case ◽  
Shoulder Injury ◽  
Work Related ◽  
Clear Cut ◽  
The Individual ◽  
Causation Analysis ◽  
Injury Causation ◽  
Relevant Factors

Abstract In most cases of shoulder injury at work, causation analysis is not clear-cut and requires detailed, thoughtful, and time-consuming causation analysis; traditionally, physicians have approached this in a cursory manner, often presenting their findings as an opinion. An established method of causation analysis using six steps is outlined in the American College of Occupational and Environmental Medicine Guidelines and in the AMA Guides to the Evaluation of Disease and Injury Causation, Second Edition, as follows: 1) collect evidence of disease; 2) collect epidemiological data; 3) collect evidence of exposure; 4) collect other relevant factors; 5) evaluate the validity of the evidence; and 6) write a report with evaluation and conclusions. Evaluators also should recognize that thresholds for causation vary by state and are based on specific statutes or case law. Three cases illustrate evidence-based causation analysis using the six steps and illustrate how examiners can form well-founded opinions about whether a given condition is work related, nonoccupational, or some combination of these. An evaluator's causal conclusions should be rational, should be consistent with the facts of the individual case and medical literature, and should cite pertinent references. The opinion should be stated “to a reasonable degree of medical probability,” on a “more-probable-than-not” basis, or using a suitable phrase that meets the legal threshold in the applicable jurisdiction.

scholarly journals Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

2021 ◽  
Vol 13 (8) ◽  
pp. 1409
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Peng Zhang
Keyword(s):  
Water Vapor ◽  
Weather Forecasting ◽  
Water Cycle ◽  
Correlation Coefficients ◽  
Support Vector ◽  
Vapor Density ◽  
Measurement Resolution ◽  
Sensing Model ◽  
Numerical Weather Forecasting ◽  
Mean Square Errors

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.

Judicial Lawmaking, Discourse Theory, and the ICTY on Belligerent Reprisals

2011 ◽  
Vol 12 (5) ◽  
pp. 1261-1278 ◽  
Author(s):  
Milan Kuhli ◽  
Klaus Günther
Keyword(s):  
International Criminal Court ◽  
International Criminal ◽  
International Criminal Tribunal ◽  
Individual Case ◽  
Criminal Court ◽  
Discourse Theory ◽  
Criminal Courts ◽  
Normative Expectations ◽  
Judicial Lawmaking ◽  
The Individual

Without presenting a full definition, it can be said that the notion of judicial lawmaking implies the idea that courts create normative expectations beyond the individual case. That is, our question is whether courts' normative declarations have an effect which is abstract and general. Our purpose here is to ask about judicial lawmaking in this sense with respect to international criminal courts and tribunals. In particular, we will focus on the International Criminal Tribunal for the Former Yugoslavia (ICTY). No other international criminal court or tribunal has issued so many judgments as the ICTY, so it seems a particularly useful focus for examining the creation of normative expectations.

Assessing the validity of NART-estimated premorbid IQs in the individual case

1990 ◽  
Vol 29 (4) ◽  
pp. 435-436 ◽  
Author(s):  
J. R. Crawford ◽  
K. M. Allan ◽  
R. H. B. Cochrane ◽  
D. M. Parker
Keyword(s):  
Individual Case ◽  
The Individual

Polycrystalline Silicon Gettering Layers with Controlled Residual Stress

2013 ◽  
Vol 205-206 ◽  
pp. 284-289 ◽  
Author(s):  
David Lysáček ◽  
Petr Kostelník ◽  
Petr Pánek
Keyword(s):  
Residual Stress ◽  
Vapor Deposition ◽  
Polycrystalline Silicon ◽  
Opposite Sign ◽  
Chemical Vapor ◽  
Pressure Chemical ◽  
Novel Method ◽  
The Individual ◽  
Scanning Electron

We report on a novel method of low pressure chemical vapor deposition of polycrystalline silicon layers used for external gettering in silicon substrate for semiconductor applications. The proposed method allowed us to produce layers of polycrystalline silicon with pre-determined residual stress. The method is based on the deposition of a multilayer system formed by two layers. The first layer is intentionally designed to have tensile stress while the second layer has compressive stress. Opposite sign of the residual stresses of the individual layers enables to pre-determine the residual stress of the gettering stack. We used scanning electron microscopy for structural characterization of the layers and intentional contamination for demonstration of the gettering properties. Residual stress of the layers was calculated from the wafer curvature.

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

Assessment ◽  
2021 ◽  
pp. 107319112110392
Author(s):  
Lars Klintwall ◽  
Martin Bellander ◽  
Matti Cervin
Keyword(s):  
Clinical Utility ◽  
Treatment Success ◽  
Centrality Measures ◽  
Retest Reliability ◽  
Causal Relations ◽  
Future Studies ◽  
Causal Networks ◽  
Novel Method ◽  
The Individual ◽  
Test Retest Reliability

Personalized case conceptualization is often regarded as a prerequisite for treatment success in psychotherapy for patients with comorbidity. This article presents Perceived Causal Networks, a novel method in which patients rate perceived causal relations among behavioral and emotional problems. First, 231 respondents screening positive for depression completed an online Perceived Causal Networks questionnaire. Median completion time (including repeat items to assess immediate test–retest reliability) was 22.7 minutes, and centrality measures showed excellent immediate test–retest reliability. Networks were highly idiosyncratic, but worrying and ruminating were the most central items for a third of respondents. Second, 50 psychotherapists rated the clinical utility of Perceived Causal Networks visualizations. Ninety-six percent rated the networks as clinically useful, and the information in the individual visualizations was judged to contain 47% of the information typically collected during a psychotherapy assessment phase. Future studies should individualize networks further and evaluate the validity of perceived causal relations.

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