Attributes of Forecast Quality

2019 ◽  
pp. 849-892
Author(s):  
A. Allen Bradley ◽  
Julie Demargne ◽  
Kristie J. Franz
Keyword(s):  
Forecast Quality

The Forecast Quality of CBOE Implied Volatility Indexes

2003 ◽  
Author(s):  
Charles J. Corrado ◽  
Thomas W. Miller
Keyword(s):  
Implied Volatility ◽  
Forecast Quality

scholarly journals Spin-up time from switching the microphysics scheme in the assimilation cycle and impacts on the precipitation forecast quality

2021 ◽  
Author(s):  
Sven Ulbrich ◽  
Christian Welzbacher ◽  
Kobra Khosravianghadikolaei ◽  
Michael Hoff ◽  
Alberto de Lozar ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Lead Time ◽  
Weather Prediction ◽  
Radar Data ◽  
Precipitation Forecast ◽  
Additional Measure ◽  
Microphysics Scheme ◽  
Numerical Weather ◽  
Complementary Approach ◽  
Forecast Quality

<p>The SINFONY project at Deutscher Wetterdienst (DWD) aims to produce seamless precipitation forecast products from minutes up to 12 hours, with particular focus on convective events. While the near future predictions are typically from nowcasting procedures using radar data, the numerical weather prediction (NWP) aims at longer time scales. The lead-time in the latest available forecast is usually too long for merging both the nowcasting and NWP output to produce reliable seamless predictions.</p><p>At DWD, the current forecasts are produced by the short range numerical weather prediction (SRNWP) <span>making use of a</span> continuous assimilation cycle with relatively long cutoff times and using 1-moment microphysics. In order to reduce the differences in the precipitation to the <span>nowcasting </span>on the NWP side, we use two different approaches. First, we reduce the lead-time from the model start by running 1-hourly forecasts based on an assimilation cycle with shorter data cutoff. Secondly, we use new observational systems in the assimilation cycle, such as radar or satellite data to capture and represent strong convective activity. This procedure is called Rapid Update Cycle (RUC). As an additional measure, we introduce a 2-Moment microphysics scheme into the numerical model, resulting in a better representation of the radar reflectivities. In order to keep the model state similar to that of the SRNWP, the RUC is a time limited assimilation cycle starting from forecasts of the SRNWP at pre-defined times.</p><p>The introduction of the 2-Moment scheme leads to a spin-up affecting both the assimilation cycle and the short forecasts. The resulting effects are analysed by comparison with the corresponding assimilation cycle using the 1-Moment scheme. As a complementary approach for the analysis, the routine cycle is run with the 2-Moment scheme. The forecast quality is used as a measure to compare the results with respect to precipitation and additional observed parameters. It is shown in how far the resulting improvements are related to the assimilation and momentum scheme, or to the higher frequency of forecasts.</p>

scholarly journals Artificial Neural Network Based shafts surface pressures Analysis

2021 ◽  
Vol 2089 (1) ◽  
pp. 012046
Author(s):  
B V Ramana Murthy ◽  
Vuppu Padmakar ◽  
B N S M Chandrika ◽  
Satya Prasad Lanka
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Neural System ◽  
Scientific Model ◽  
System Models ◽  
Learning Rules ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Forecast Quality

Abstract This paper exhibits a development of an Artificial Neural Network (ANN) as an instrument for investigation of various parameters of a framework. ANN comprises of various layers of straightforward handling components called as neurons. The neuron performs two capacities, to be specific, assortment of sources of info and age of a yield. Utilization of ANN gives diagram of the hypothesis, learning rules, and uses of the most significant neural system models, definitions and style of Computation. The scientific model of system illuminates the idea of sources of info, loads, adding capacity, actuation work and yields. At that point ANN chooses the sort of learning for modification of loads with change in parameters. At long last the examination of a framework is finished by ANN execution and ANN preparing and forecast quality.

Power consumption forecast quality assessment

2018 ◽  
Author(s):  
Constantin Barbulescu ◽  
Stefan Kilyeni ◽  
Antheia Deacu ◽  
Attila Simo ◽  
Mihaela Craciun
Keyword(s):  
Power Consumption ◽  
Quality Assessment ◽  
Forecast Quality

Analysis of the Criteria for Assessing the Forecast Quality of Industrial Safety Indicators of Enterprises

2021 ◽  
Vol 17 (6) ◽  
pp. 519
Author(s):  
Bogdanova Leila M. ◽  
Nagibin Sergey Ya. ◽  
Chemakin Alexander S.
Keyword(s):  
Industrial Safety ◽  
Forecast Quality

The Weather Roulette: A Game to Communicate the Usefulness of Probabilistic Climate Predictions

2019 ◽  
Vol 100 (10) ◽  
pp. 1909-1921 ◽  
Author(s):  
Marta Terrado ◽  
Llorenç Lledó ◽  
Dragana Bojovic ◽  
Asun Lera St. Clair ◽  
Albert Soret ◽  
...  
Keyword(s):  
Decision Making ◽  
Return On Investment ◽  
Climate Science ◽  
Skill Score ◽  
Economic Benefits ◽  
Business Sector ◽  
Weather Forecasts ◽  
Climate Anomalies ◽  
Forecast Quality

AbstractClimate predictions, from three weeks to a decade into the future, can provide invaluable information for climate-sensitive socioeconomic sectors, such as renewable energy, agriculture, or insurance. However, communicating and interpreting these predictions is not straightforward. Barriers hindering user uptake include a terminology gap between climate scientists and users, the difficulties of dealing with probabilistic outcomes for decision-making, and the lower skill of climate predictions compared to the skill of weather forecasts. This paper presents a gaming approach to break communication and understanding barriers through the application of the Weather Roulette conceptual framework. In the game, the player can choose between two forecast options, one that uses ECMWF seasonal predictions against one using climatology-derived probabilities. For each forecast option, the bet is spread proportionally to the predicted probabilities, either in a single year game or a game for the whole period of 33 past years. This paper provides skill maps of forecast quality metrics commonly used by the climate prediction community (e.g., ignorance skill score and ranked probability skill score), which in the game are linked to metrics easily understood by the business sector (e.g., interest rate and return on investment). In a simplified context, we illustrate how in skillful regions the economic benefits of using ECMWF predictions arise in the long term and are higher than using climatology. This paper provides an example of how to convey the usefulness of climate predictions and transfer the knowledge from climate science to potential users. If applied, this approach could provide the basis for a better integration of knowledge about climate anomalies into operational and managerial processes.

scholarly journals Forecasting water consumption in towns of different sizes

2019 ◽  
Vol 100 ◽  
pp. 00064
Author(s):  
Adam Piasecki ◽  
Agnieszka Pilarska ◽  
Radosław Golba
Keyword(s):  
Water Consumption ◽  
Principal Component ◽  
Regression Method ◽  
Supply System ◽  
Short Term ◽  
Individual Model ◽  
Explanatory Variables ◽  
Multiple Regression Method ◽  
The Town ◽  
Forecast Quality

The aim of the work was to compare water consumption forecasting in two towns of different sizes. The objects of research were the town of Toruń and the town of Żnin in central Poland. Two models were built for each. The models were constructed using the multiple regression method. In constructing the models, explanatory variables determined by Principal Component Analysis (PCA) were used. The set of explanatory variables identified to construct each individual model differed. The models for Toruń obtained better forecast quality assessment criteria values. This was mainly due to the water supply system in the small town (Żnin) being less resilient to sudden, short-term changes in consumers’ water use. At the same time, the importance of the location of the meteorological stations from which data was taken to build the model was emphasised.

scholarly journals The Generalized Discrimination Score for Ensemble Forecasts

2011 ◽  
Vol 139 (9) ◽  
pp. 3069-3074 ◽  
Author(s):  
Andreas P. Weigel ◽  
Simon J. Mason
Keyword(s):  
Binary Outcomes ◽  
Continuous Variables ◽  
Discrimination Score ◽  
Ensemble Forecasts ◽  
Probabilistic Forecasts ◽  
Forecast Quality

This article refers to the study of Mason and Weigel, where the generalized discrimination score D has been introduced. This score quantifies whether a set of observed outcomes can be correctly discriminated by the corresponding forecasts (i.e., it is a measure of the skill attribute of discrimination). Because of its generic definition, D can be adapted to essentially all relevant verification contexts, ranging from simple yes–no forecasts of binary outcomes to probabilistic forecasts of continuous variables. For most of these cases, Mason and Weigel have derived expressions for D, many of which have turned out to be equivalent to scores that are already known under different names. However, no guidance was provided on how to calculate D for ensemble forecasts. This gap is aggravated by the fact that there are currently very few measures of forecast quality that could be directly applied to ensemble forecasts without requiring that probabilities be derived from the ensemble members prior to verification. This study seeks to close this gap. A definition is proposed of how ensemble forecasts can be ranked; the ranks of the ensemble forecasts can then be used as a basis for attempting to discriminate between corresponding observations. Given this definition, formulations of D are derived that are directly applicable to ensemble forecasts.

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