Mine-Weather combines data from various weather sources and determines forecast accuracy...Read More
Playing a critical role in industrial applications for both capacity planning and utilization under...Read More
Several complexities associated in linking forecast data to observational data are simplified using rules...Read More
Scoring algorithms based on statistical methods are employed to verify relevant weather attributes...Read More
Summarizing the enormous volumes of weather forecast data into a uniform format for processing...Read More
Providing analytical reports using reporting framework such as report worksheets, interactive ...Read More
Determine accurate weather forecasts at critical time periods during extreme weather conditions, like storm...Read More
Mine-Weather can be leveraged to forecast accuracy of utility’s outage prediction model (OPM)Read More
Scoring algorithms based on statistical methods to be incorporated into the Mine-Weather platform...Read More
Companies across several industries heavily rely on weather forecasts to plan their activities and preparedness during adverse weather conditions. Mine-Weather is an analytical database and visualization system designed to probe the accuracy of the weather forecasts. Mine-Weather comprises an analytical database and several visualization dashboards. It combines several weather forecast sources with observation data from numerous sites distributed throughout the service area of the utility and draws-up a scoreboard for comparison.
Download this paper to read more about what Mine-Weather’s features and benefits.
Companies across several industries such as utility and construction need to plan their activities based on the accuracy of weather forecasts. Mine-Weather application provides weather variables, thresholds and time periods to meets specific forecast accuracy requirements for a number of different industrial applications. Mine-Weather has a highly adaptable analytical database that provides site-specific, near real-time, weather forecast analysis enabling industries to optimize production schedules and take safety precautions well in advance of inclement weather. It facilitates preparedness and capacity planning in advance of the weather event.
Download this paper to find out various applications of Mine-Weather in several industries.
Numerous complexities are associated with linking of forecast data to observational data, which involves a myriad of data issues that need to be addressed. Mine-Weather simplifies this process as it adheres to a set of general rules regarding capturing and storing forecast and observational data, migration of historical data and calculating scores at the most granular levels. In order to obtain accurate scores, it is critical that time and attention be paid to mapping the right fields between forecasts and observations. Mine-Weather uses advanced table mapping techniques and takes a standardized approach in comparing forecasts and actual data at the transition point.
Download this paper to see how Mine-Weather simplifies the various data linking complexities.
Adapting well established methods using scoring algorithms make weather forecasting easier to understand and evaluate. Mine-Weather uses a number of scoring models based on statistical methods to verify relevant weather attributes in the form of scores. Numerical contingency scoring model helps evaluate the overall forecast performance on specific geographies across long periods of time. Likewise, forecast performance for individual weather attributes like temperature, wind gust or snow fall can be measured in short time intervals prior to a particular type of event. Decision makers are equipped with hourly and daily forecasts to measure the accuracy across one or all weather variables.
Download this paper to understand various Mine-Weather scoring models.
Mine-Weather summarizes a large amount of weather forecast and observational data by converting it into a suitable format for analysis. Robust scoring algorithms transform the raw weather data to accurate scores by normalizing and summarizing the data in real-time. Mine-Weather leverages a powerful combination of automated data extraction, transformation and loading processes that eliminates a lot of issues related to data transformation. Tableau data analysis and visualization tool is used for further data mining and reporting of the formatted data.
Download this paper to learn more about how Mine-Weather normalizes and summarizes weather forecast data.
Mine-Weather’s analytical reporting framework enables comparison of different weather parameters to arrive at accurate results. It employs various types of reporting formats, filtering and data-grouping approaches. Interactive filters and calculated metrics are applied to further drill down and churn out critical reports. Reporting framework encompasses a range of supported data visualization tools that analysts can use to present reports in a simple and intuitive format that easily blends with the end user interface.
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Accurate weather forecasts during extreme weather conditions are critical as they provide better impact-based decision support for companies across various industries. Mine-Weather focuses on forecast accuracy specifically during a storm event. It uses a time based and weather based threshold approach. In time based approach, forecast scenarios related to a storm are executed at different time periods to access its accuracy. For weather based threshold approach, conditions are defined and threshold value is set based on the weather variables (like wind speed, temperature, rainfall) to determine extreme weather. Mine-Weather isolates all forecast data collected for a particular time period and analyses to see the forecast accuracy during a storm condition.
Download this paper to read the first series of Mine-Weather to determine accuracy of forecast data during a storm event.
Macrosoft’s Mine-Weather is a flexible analysis platform designed for utilities to asses forecast accuracy under different weather conditions. Electric utilities have always been on a look out to assess the accuracy of their weather forecasts, as they need to plan out their activities and preparedness during an extreme event. Let’s see how we can leverage the power of Mine-Weather to not only asses the accuracy of a utility’s weather prediction, but also to forecast accuracy of a utility’s outage prediction model (OPM).
Download this paper to learn more about Mine-Weather electric utility outage prediction models.
We have developed various advanced scoring algorithms based on statistical methods to be incorporated into the Mine-Weather platform. This is the first among the three papers that we consider to start a discussion on the advanced methods, by setting up a conceptual framework that focuses all our thinking on weather forecast verification. Alongside, we will be aiming for a more refined and precise statistical algorithms that will help us decide on which method is more suitable for including in future releases of Mine-Weather. We hope the advanced scoring algorithms will allow decision makers judge the confidence in the weather forecasts they are currently using and to evaluate possible new forecasts they are considering to add.
Download this paper to learn more about the first series of advanced Weather Verification Scoring Algorithms.
In this second series, we provide a detailed description of the weather scoring algorithms currently incorporated into the Mine-Weather system. It uses a number of scoring models based on statistical methods to verify weather attributes (temperature, precipitation, wind speed/gust, etc.) in the form of scores. When considering numeric variables (point forecasts like temperature, % forecast Humidity, etc.) the scoring is based on the numeric comparisons of forecasted values against the observed actuals. For dichotomous attributes, we compare the forecasts against actuals by using statistical contingency tables as the basis for the score calculations. Mine-Weather also has capabilities for verifying special Weather Events (hurricanes, winter storms, etc.) that are of great importance to utilities.
Download this paper to learn more about the second series of advanced Weather Verification Scoring Algorithms.
Macrosoft is excited to announce the release of our new version of Mine-Weather 2.0 application, which is fully cloud-based and resides on the Microsoft Azure cloud platform. Apart from being cloud based, Mine-Weather 2.0 also contains a number of new advanced features and many new scoring algorithms that provide a more accurate estimate of weather forecasts. After we engage in an initial short configuration phase a new client can access all their weather forecast and actual data from the cloud and immediately begin exploratory studies on weather forecast accuracy. Finally, the new Mine-Weather system has the capability to assess the accuracy of solar, wind, and electric demand forecasts using the same system.
Download this paper to learn more about our new Cloud-Based SAAS Platform with Advanced Features and Scoring Algorithms.
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