Weather Monitoring

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General description

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

The weather monitoring module is one of the five modules of the MCYFS and can be split in 3 procedures.

  1. Acquisition
  2. Interpolation
  3. Aggregated

The output of the weather monitoring module is used in two ways. In the first place as input for the crop simulation module to simulate crops behaviors and evaluate the effects of weather on crops yields. Secondly as weather indicators for a direct evaluation of alarming situations such as drought, extreme rainfall during sowing, flowering or harvest etc. For this purpose the weather data are also input for calculating climatology.


Observed weather

File:Acquisition of observed weather.jpg
Acquisition of observed weather

Every day the raw data of at least 3000 stations that regularly collect and supply one or more indicators are acquired and added to the raw station weather database. For the year 2010 over 3400 stations have contributions to the database. Over time another 2800 stations have a usefull archive. Basic indicators that are collected include:

  • Precipitation (daily and 6-hourly)
  • Temperature (daily maximum, daily minimum and 3-hourly)
  • Measured radiation
  • Sunshine
  • Cloud cover
  • Vapour pressure
  • Wind speed
  • Snow depth
  • Humidity (3-hourly)

The archive data and near real time incoming indicator values are checked for errors such as temperatures that are too low or indicator values that don't change over time. Errors are corrected and the data are converted to daily values that fit in a uniform station weather database.

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Some indicators that are needed in the crop simulation module are not sufficiently measured by weather stations. These advanced indicators are calculated from basic indicators:

  • Calculated radiation at surface
  • Transpiration of water surface
  • Transpiration of wet bare soil
  • Evapotranspiration

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Forecasted weather

Instead of loading observed weather data in the system also weather forecasts data are loaded. This has the advantage that crop yield can be simulated into the future (see Crop Simulation) which is closer to the end of the crop season (compared to observation based simulations) and can be used to make Yield Forecasts (see Yield Forecasting).

5 weather forecast products from ECMWF are loaded into the system:

  • Analysis model
  • Deterministic forecast model
  • Ensemble Prediction System
  • Monthly forecast model
  • Seasonal forecast model

These products have a different number of forecast days and a varying number of possible results called 'members'. Different members can thought of as model runs with a slightly different initialization and thus slightly different forecast results.

Model Abbreviation Number of forecast days Members Horizontal model resolution* Acquired resolution** Delivery
Analysis model HIS 1 1 ~16km 0.25° x 0.25° Daily (10.30 hr)
Deterministic forecast model OPE 10 1 ~16km 0.25° x 0.25° Daily (12.00 hr)
Ensemble Prediction System EPS 15 51 ~30km / ~60km*** 0.5° x 0.5° Daily (14.00 hr)
Monthly forecast model MON 32 50 ~30km / ~60km*** 0.5° x 0.5° Every Friday (03.00 hr)
Seasonal forecast model SEA 170 40 ~150km 0.25° x 0.25° Every 15th of the month (14.00 hr)

* Horizontal model resolution: resoltion in which the model simulates the weather indicators. The points for which the indicators are simulated are distributed over the earth using a Reduced Gaussian grid.
** Acquired resolution: resolution in which the simulated indicators are acquired en loaded into the MCYFS. The simulated indicators are distributed over the earth using a WGS84 coordinate system.
*** The first 10 days are simulated with a ~30km resolution. The remaining days on a ~60km resolution

For the HIS model only the forecast for the current day is processed (number of forecast days = 1) as best estimator for weather indicators of a day. In this way an archive is build up from current day forecasts equivalent to the archive of observed station weather. The data of other models are completely replaced when a more recent data set becomes available (OPE, EPS, MON and SEA). These later models are not kept as alternative archives. Therefore only the HIS data can be used for calculating climatolgy.

The acquired basic indicators are:

  • Precipitation
  • Temperature (daily maximum, minimum and average)
  • Dewpoint temperature
  • Global radiation
  • Snow depth
  • Wind speed

Advanced indicators that are calculated from basis indicators:

  • Vapour pressure
  • Transpiration of water surface
  • Transpiration of wet bare soil
  • Evapotranspiration

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observed weather

Observed weather is aquired from weather stations that have an iragular distribution over Europe. Weather station data of a single station is only representative for the location of that station. To construct weather data for locations inbetween stations a conversion is needed. interpolation is one of the methods to do this. In the MCYFS this procedure is used to converts iregular distrubuted station data to regular distributed data. The regular distribution is organized as a grid with side by side grid cells of 25 kilometer wide and 25 kilometer long that cover the European continent and is called the regular climatic grid.

The interpolation is managed by a sub-system called CGMS.


More information

File:Interpolation of observed weather.jpg
Interpolation of observed weather

Current year
In the current year (and in near real time) for every day and each grid cell up to the 4 most suitable weather stations are selected. The selection is based on comparing the station locations and altitudes with the grid cell location and altitude. The suitable stations differ between grid cells. They also may differ between days and even between indicators. Only the suitable weather stations are used to interpolate the weather data to the specific grid cell on the specific day. In case no suitable stations are found, a long term average value is substituted to ensure spatial and temporal continuity.

Previous years (the archive)
For interpolation of archive station weather each grid cell uses the same suitable stations for a complete year. For most recent years around 2700 stations have a sufficient temporal coverage (enough observations within one year). Only these are used in the interpolation procedure. In this way a grid weather archive is build up with daily weather for each grid cell going back to 1975.

With the grid weather database available, other weather indicators can be derived:

  • average day temperature
  • climatic water balance
  • long term average indicators (climatolgy)

Some of the weather indicators are defined over an arbitrary period and can only be calculated on the fly with special tools such as the Marsop3 viewer:

  • sum, max, min and average of an indicator
  • number of heat waves
  • longest heat wave period
  • number of hot day's
  • number of cold day's
  • number of day's with significant rainfall

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Forecasted weather

Example of 0.5 x 0.5 degrees source grid of the ECMWF EPS and MON model (black dots) and 25 x 25 km regular climate grid (gray lines)

The data of different forecast models ('source') are acquired in different spatial resolutions and projections (sea 'Acquisition'). They have a regular distribution but it is different from the regular distribution used in the MCYFS. Therefore the data are interpolated from 'source' grid to 'target' grid that is equal to the climate grid explained in Interpolation. This specific interpolation procedure is also called 'downscalling' because for the EPS, MON and SEA models it converts lower resolution source data into higher resolution data.

In the first part of the downscalling method parameter values for a target gridcell are derived from the 4 closest source gridcells where closer source gridcells have a higher weight (inverse distance weighting).

In the second part of the downscalling a correction is made for systematic bias (systematic deviations between estimated downscalled source data and observed target data). For instance: temperature is correlated with height. The heigt values in the source grid are different from the height values in the target grid (they sample different locations). Therefor downscalled temperature will be biased depending upon the height differences, even if corrections are applied for height differences.

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Example of 4 different administrative levels in combination with landcover type 'arable land' on 25 x 25 km grid.

The primary results of the interpolating observed stations weather and downscalled forecast weather is grid weather. To answer questions like:

'What was the average temperature in France during the last week for locations where winter wheat is grown?'

the grid weather data are aggregated to different levels of administrative regions and different levels of agri-environmental regions while weighting each gridcells for the area covered by a certain crop or landcover type. Observed grid weather and forecasted grid weather of the ECMWF HIS, OPE and EPS models are aggregated to:

  • 4 levels of administrative regions for 12 crops and 7 landcover types
  • 2 levels of agri-environmental regions for 7 landcover types.

The aggregation of the EPS model is restricted to the median of all EPS member values per forecast day. All these combinations are aggregated a second time with the difference that only gridcells are taken into account that have at least 5 % coverage of a certain crop or landcover type. For example:

  • administrative region: 'country' level
  • landcover type: 'arable land'
  • threshold: 5%

In this combination all grid cells that have at least 5% coverage of landcover type 'arable land' contribute to the aggregated values for 'countries' they are contained by. The contribution of each grid cell that passes the threshold of 5% is weighted by the area covered with landcover type 'arable land'. Grid cells with less than 5% coverage are not taken into account.

Altogether the aggregation procedure makes 720 combinations of weather type (Observed, HIS, OPE, EPS), regions (4 administrative levels, 2 agri-environmental levels), landcover type (12 crop and 7 landcovers) and threshold (0%, 5%) available.

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Climatology (long term average weather)

Within the MCYFS climatology is considered as long term average values of weather indicators. It is essential to understand how current weather conditions relate to the normal situation. Long term average values are calculated for observed weather and forecasted weather (HIS model only) of different resolutions (25 x 25 km regular climate grid, 4 administrative regions and 2 agri-environmental regions).

The following parameters are available:

  • Precipitation
  • Temperature (daily maximum, minimum and average)
  • Dewpoint temperature (forecasted weather only)
  • Vapour pressure
  • Wind speed
  • Snow depth
  • Calculated radiation at surface (observed), global radiation (forecasted)
  • Transpiration of water surface
  • Transpiration of wet bare soiles
  • Evapotranspiration
  • fraction of days with daily maximum temperature greater than 25 degrees celsius
  • fraction of days with daily maximum temperature greater than 30 degrees celsius
  • fraction of days with daily maximum temperature greater than 35 degrees celsius
  • fraction of days with daily maximum temperature less than 0 degrees celsius
  • fraction of days with daily maximum temperature less than minus 8 degrees celsius
  • fraction of days with daily maximum temperature less than minus 10 degrees celsius
  • fraction of days with daily maximum temperature less than minus 18 degrees celsius
  • fraction of days with daily maximum temperature less than minus 20 degrees celsius
  • fraction of days with rainfall greater than 5 mm
  • fraction of days with rainfall greater than 10 mm
  • fraction of days with rainfall greater than 15 mm
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