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The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy of different time series forecasting methods. They are organized by teams led by forecasting researcher Spyros Makridakis and were first held in 1982. [1] [2] [3] [4]
The MM5 is a limited-area, terrain-following sigma coordinate model that is used to replicate or forecast mesoscale and regional scale atmospheric circulation. [1] It has been updated many times since the 1970s to fix bugs, adapt to new technologies, and work on different types of computers and software.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The Weather Research and Forecasting (WRF) Model [1] (/ ˈ w ɔːr f /) is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. NWP refers to the simulation and prediction of the atmosphere with a computer model, and WRF is a set of software for this.
The Global Energy Forecasting Competition (GEFCom) is a competition conducted by a team led by Dr. Tao Hong that invites submissions around the world for forecasting energy demand. [1] GEFCom was first held in 2012 on Kaggle , [ 2 ] and the second GEFCom was held in 2014 on CrowdANALYTIX.
The software has been used to model real-time weather as well as seasonal forecasting of convection, tornadoes [3] and tropical cyclones. [4] The atmospheric modeling component of the software can be used with other atmospheric modeling software including the Weather Research and Forecasting Model , the Global Forecast System , and the ...
ECMWF aims to provide accurate medium-range global weather forecasts out to 15 days and seasonal forecasts out to 12 months. [11] Its products are provided to the national weather services of its member states and co-operating states as a complement to their national short-range and climatological activities, and those national states use ECMWF's products for their own national duties, in ...
This method of forecasting can improve forecasts when compared to a single model-based approach. [18] When the models within a multi-model ensemble are adjusted for their various biases, this process is known as "superensemble forecasting". This type of a forecast significantly reduces errors in model output. [19]