Difference between revisions of "Weather Monitoring"
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*[[Time series analysis at station, grid and regional level]] | *[[Time series analysis at station, grid and regional level]] | ||
*[[Future developments: cgms numerical weather based]] | *[[Future developments: cgms numerical weather based]] | ||
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| + | ====Climatology==== | ||
| + | Climatology is essential to understand how current weather conditions relate to the normal situation. Long term average values are available for the observed and forecasted weather at different spatial levels like the 25 km grid, administrative regions and agri-environmental regions. | ||
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| + | Detailed information on page: | ||
| + | *[[Calculation of Climatology]] | ||
Revision as of 10:01, 16 July 2010
Contents
General description
The weather monitoring module is one of the main elements of the MCYFS. Main input into the module are weather station observations and forecast data.
The module contains 4 procedures. The first procedure handles data aquisition and quality check of the data. The second procedure interpolates the cleaned station weather to a 25x25km grid. A third procedure downscales the forecast weather from ECMWF to the same 25x25km grid. And finally the grid weather from observations and forecasts is aggregated to regions.
Daily weather data is used in two ways for crop yield evaluations. In the first place as input for the crop growth model WOFOST to simulate crops behaviors and evaluate the effects of weather on crops yields at European level (see Crop Simulation). Secondly as weather indicators for a direct evaluation of alarming situations such as drought, extreme rainfall during sowing, flowering or harvest etc.
The crops behaviors are mainly influenced by the atmospheric conditions near the earth surface. Considering the data availability, resources and purpose of the system a time scale of one day and a spatial scale of 25x25km are chosen as the resolutions to estimate crop yields at European scale.
Acquisition, available stations and quality check
Around 3000 stations that regularly collect data and that also can supply the data in near real time are used in the daily processing. Another ##### available stations have have a usefull archive. Both the archive data and near real time incoming data is checked for errors such as temperatures that are too low or too hight or values that don't change over time.
Detailed information on other pages:
Interpolation to 25x25km grid
The interpolation is managed by a sub-system called Crop Growth Monitoring System (CGMS). For each grid cell every day the most suitable stations are selected and used to interpolate a grid value. From day to day and from weather indicator to weather indicator different stations can be used. In this way an archive is build up with daily weather for each grid cell. The archive goes back to 1975.
All input data and output data of CGMS is stored in a relational database of which the structure is presented in Appendix 4. Individual tables are described in Appendix 5. Procedures may be stored as database objects, scripts or separate software packages. A detailed description of the software procedures can be found in Appendix 3.
Detailed information on other pages:
Downscalling to 25x25km grid
Different forecast products from ECMWF are loaded into the system:
| Model | Forecast days | Members | Spatial resolution | Delivery |
|---|---|---|---|---|
| Analysis model | 1 | 1 | 0.25° x 0.25° | Daily (10.30 hr) |
| Deterministic forecast | 10 | 1 | 0.25° x 0.25° | Daily (12.00 hr) |
| Ensemble Prediction System | 15 | 51 | 0.5° x 0.5° | Daily (14.00 hr) |
| Monthly forecast | 32 | 50 | 0.5° x 0.5° | Every Friday (03.00 hr) |
| Seasonal forecast | 170 | 40 | 0.25° x 0.25° | Every 15th of the month (14.00 hr) |
Inverse Distance Weighting (IDW) is used to convert the data to a 25x25km grid. Only the Analysis model is archived. All other forecasts are overwritten whenever a new one is available. In this way an archive is build up with daily model weather for each grid cell going back to 1989.
Detailed information on other pages:
Aggregation to regions
'What was the average temperature in France during the last week?'
To answer a question like this, grid weather data is aggregated to regions:
- Four levels of administrative regions (NUTS regions)
- Two levels of agri-environmental regions (Metzger et. al., 2005)
'What was the average temperature in France during the last week where winter wheat is grown?'
To answer this question crop specific aggregations are calculated. Crop masks are used to decide which grid cells should be taken into account.
Detailed information on other pages:
- Analysis of weather indicators
- Time series analysis at station, grid and regional level
- Future developments: cgms numerical weather based
Climatology
Climatology is essential to understand how current weather conditions relate to the normal situation. Long term average values are available for the observed and forecasted weather at different spatial levels like the 25 km grid, administrative regions and agri-environmental regions.
Detailed information on page:
