. . . "Acquire the language, terminology and methods of data assimilation."@en . . "Acquire the language, terminology and methods of data assimilation."@en . . . "Apply practical data assimilation techniques to improve hydrometeorological modelling and predictions."@en . . "Apply practical data assimilation techniques to improve hydrometeorological modelling and predictions."@en . . . "Use reanalysis data and know the limitations"@en . . "Use reanalysis data and know the limitations"@en . . . "Learn the Bayesian theory."@en . . "Learn the Bayesian theory."@en . . . "Learn the techniques for parameter estimation."@en . . "Learn the techniques for parameter estimation."@en . . "https://ltb.itc.utwente.nl/page/792/concept/152725" . . "Land and environmental modeling"@en . . . . . "https://ltb.itc.utwente.nl/page/792/concept/152836" . . "Data assimilation"@en . . . . "https://ltb.itc.utwente.nl/page/792/concept/152842" . . "Earth observation"@en . . . . . . . . "https://ltb.itc.utwente.nl/page/792/concept/152857" . . "Bayesian statistics"@en . . . . "https://ltb.itc.utwente.nl/page/792/concept/152866" . . "Numerical model"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "The Master’s Programme Geo-Information Science and Earth Observation (M-GEO) is a two-year academic curriculum at MSc level, taught fully in English, dedicated to understanding the earth’s systems from a geographic and spatial perspective. The field of Geo-information Science and Earth Observation has, in recent years, witnessed fast scientific and technological developments. As a result, geographic information has become a vital asset to society and part of our daily life. The ubiquitous production and availability of spatial data require cloud computing and new technology to turn the increasing volume of ‘big data’ to good use. The growing range of global challenges, from climate change and resource depletion to environmental pollution and pandemic diseases, that our society and in particular the more vulnerable populations on our planet are facing, increases the demand for academic professionals who have the ability, attitudes and skills to design solutions that are sustainable, transdisciplinary and innovative with positive societal impacts. Our education focuses on addressing these global problems by means of advanced geo-information and earth observation applications."@en . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . . . "Linux"@en . . . "Matlab"@en . . . "Course"@en . "201900071" . "WRS_0002" . "5"^^ . "140"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "online" . "Lectures, practicals (workshops), tutorials, individual assignment and group work and written tests."@en . "Knowledge of Programming and skills to work on a server in LINUX environment are beneficial for the learning process ,Successful completion of year 1 M-GEO WREM specialization courses, or equivalent."@en . "4"^^ . "2" . "1B " . "2022-11-13T23:00:00Z"^^ . "Data assimilation is a standard practice in numerical weather prediction (e.g., as implemented in the European Centre for Medium-Range Weather Forecasts, ECMWF), and is increasingly used in many other areas of climate, atmosphere, ocean, land and environment modeling.\n\nData Assimilation is a process in which observations are assimilated into a dynamical numerical model in order to determine as accurately as possible the state of the physical system. This course will introduce the theoretical background, the state-of-the-art methods and practical systems, and examples of data assimilation."@en . "Data Assimilation "@en . "Data Assimilation "@en . "Data Assimila