Difference between revisions of "Weather Monitoring"

From Agri4castWiki
Jump to: navigation, search
(Downscalling forecast weather to 25x25km grid)
(Downscalling forecast weather to 25x25km grid)
Line 49: Line 49:
 
|}
 
|}
  
 
+
For every cell in the 25x25km target grid, an inverse distance interpolation (also called [http://en.wikipedia.org/wiki/Inverse_distance_weighting Inverse Distance Weighting, IDW]) for all weather variables and altitude is done to the 4 nearest cells.
  
 
Detailed information on other pages:
 
Detailed information on other pages:

Revision as of 15:02, 15 July 2010

Introduction

The weather monitoring module is one of the main elements of the MCYFS. It is divided in three categories:

  • data bases
  • data fluxes
  • procedures

The data bases store the input data and output data. The data fluxes represent the flow of data from external sources to the data bases, between data bases, towards others parts of the system and to end-users (clients). The procedures manipulate the data.

File:Architecture weather monitoring.jpg
General layout of the weather monitoring components in MCYFS

General description

File:Flowchart weather monitoring.jpg
Overview of the weather monitoring components of the CGMS

The weather monitoring module contains 4 procedures constantly check for updates. The first procedure checks incoming station weather (three-hourly, six-hourly, daily) of over 3000 European weather stations with the AMDAC software. The second procedure interpolates this station weather to a 25x25km grid that completely covers the European region. A third procedure downscales the forecast weather from ECMWF to the same 25x25km grid. And finally all grid weather is aggregated to regions such as countries, provinces, departments, agri-environmental zones etc.

Quality check by AMDAC

The AMDAC software checks all incoming data for errors such as temperatures that are too low or too hight or values that don't change over time. The software automatically flags suspicious data. A meteorologist gives the final verdict based on station observations nearby.

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 forecast weather 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 1 0.25° x 0.25° Every 15th of the month (14.00 hr)

For every cell in the 25x25km target grid, an inverse distance interpolation (also called Inverse Distance Weighting, IDW) for all weather variables and altitude is done to the 4 nearest cells.

Detailed information on other pages:

Aggregation of grid weather to regions

Detailed information on other pages:

Goals and assumptions

Daily meteorological station data are 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 25 by 25 km are chosen as the resolutions to estimate crop yields at European scale.