The Environmental Data Processing Lab is an educational activity aimed at providing the basic knowledge of collecting, processing and interpreting environmental data and their application in solving water engineering problems.
It is a part of the Master Degree in "Civil Engineering for Protection against Natural Hazards", Hydraulics curriculum, which aims to train a civil engineer capable of solving design problems of land and water defense interventions.
Within the framework of this course, teaching aims to provide basic knowledge of the main methods of technical and scientific use of databases of environmental and meteorological parameters, with special reference to direct measurements and model-derived series (forecasts, hindcasts, reanalysis). At the end of the course, students will be able to use a computational language for the analysis of large amounts of data and for the production of statistical processing useful in applications.
It is a part of the Master Degree in "Civil Engineering for Protection against Natural Hazards", Hydraulics curriculum, which aims to train a civil engineer capable of solving design problems of land and water defense interventions.
Within the framework of this course, teaching aims to provide basic knowledge of the main methods of technical and scientific use of databases of environmental and meteorological parameters, with special reference to direct measurements and model-derived series (forecasts, hindcasts, reanalysis). At the end of the course, students will be able to use a computational language for the analysis of large amounts of data and for the production of statistical processing useful in applications.
teacher profile teaching materials
2. Measurements of meteo-idrorological variables
3. Major international large-scale environmental monitoring programs
4. Basics of meteorological and meteomarine modeling, hindcasting and reanalysis techniques
5. Basics of climate modeling and IPCC projections
6. Access and processing of observed and derived weather-climate data from global/regional simulation and reanalysis models (with exercises in Matlab)
7. Techniques of time series analysis of weather-climate data.
i. Data loading and time index management
ii. Data validation and elimination of anomalous records
iii. Basic statistical analysis on the total sample (e.g., duration curves)
iv. Statistical sample extraction of extreme values (Peaks Over Treshold and Block Maxima methods)
v. Fitting probability distributions to the total sample and the sample of extreme values
vi. Techniques for alignment and comparison of multiple time series, including correlation and bias analysis
Programme
1. Reference to meteo-idrorological variables2. Measurements of meteo-idrorological variables
3. Major international large-scale environmental monitoring programs
4. Basics of meteorological and meteomarine modeling, hindcasting and reanalysis techniques
5. Basics of climate modeling and IPCC projections
6. Access and processing of observed and derived weather-climate data from global/regional simulation and reanalysis models (with exercises in Matlab)
7. Techniques of time series analysis of weather-climate data.
i. Data loading and time index management
ii. Data validation and elimination of anomalous records
iii. Basic statistical analysis on the total sample (e.g., duration curves)
iv. Statistical sample extraction of extreme values (Peaks Over Treshold and Block Maxima methods)
v. Fitting probability distributions to the total sample and the sample of extreme values
vi. Techniques for alignment and comparison of multiple time series, including correlation and bias analysis
Type of evaluation
The knowledge and skills acquired will be assessed through the following: • individual or group project • practical computer-based test • technical report or reproducible notebook • oral presentation of the work completed teacher profile teaching materials
2. Major international large-scale environmental monitoring programs
3. Basics of meteorological and meteomarine modeling, hindcasting and reanalysis techniques
4. Basics of climate modeling and IPCC projections
5. Access and processing of observed and derived weather-climate data from global/regional simulation and reanalysis models (with exercises in Matlab)
6. Techniques of time series analysis of weather-climate data.
i. Data loading and time index management
ii. Data validation and elimination of anomalous records
iii. Basic statistical analysis on the total sample (e.g., duration curves)
iv. Statistical sample extraction of extreme values (Peaks Over Treshold and Block Maxima methods)
v. Fitting probability distributions to the total sample and the sample of extreme values
vi. Techniques for alignment and comparison of multiple time series, including correlation and bias analysis
Programme
1. Reference to meteo-idrorological variables and their measurement2. Major international large-scale environmental monitoring programs
3. Basics of meteorological and meteomarine modeling, hindcasting and reanalysis techniques
4. Basics of climate modeling and IPCC projections
5. Access and processing of observed and derived weather-climate data from global/regional simulation and reanalysis models (with exercises in Matlab)
6. Techniques of time series analysis of weather-climate data.
i. Data loading and time index management
ii. Data validation and elimination of anomalous records
iii. Basic statistical analysis on the total sample (e.g., duration curves)
iv. Statistical sample extraction of extreme values (Peaks Over Treshold and Block Maxima methods)
v. Fitting probability distributions to the total sample and the sample of extreme values
vi. Techniques for alignment and comparison of multiple time series, including correlation and bias analysis
Core Documentation
The teaching materials will be provided by the lecturer in the form of slides or handoutsAttendance
Attendance is not compulsory but strongly recommended.Type of evaluation
The knowledge and skills acquired will be assessed through the following: • individual or group project • practical computer-based test • technical report or reproducible notebook • oral presentation of the work completed