Meteorological data from ground stations
The stations are limited to those that regularly collect data and can supply the data in near real time (Burrill and Vossen, 1992). Relevant information of stations includes WMO station number, station name, latitude, longitude and altitude. This data is available in the table WEATHER_STATION.
Some of the historic meteorological data are purchased directly from National Meteorological Services. Others are acquired via the Global Telecommunication System (GTS). As the data are obtained from a variety of different sources, considerable preprocessing is necessary to convert them to a standard format. Two different procedures are applied for distinct subsets of the data. The historic data came directly from National Meteorological Services. Around 1992 they represented approximately 380 stations in the EU, Switzerland, Poland and Slovenia with data from 1949 to 1991 (Burrill and Vossen, 1992). Later the historic sets have been extended with stations in eastern Europe, western Russia, Maghreb and Turkey. The historic data were converted into consistent units and were checked on realistic values. The database was also scanned for inconsistencies, such as successive days with the same value for a variable, or minimum temperatures higher than maximum temperatures (Burrill and Vossen, 1992).
From 1991 to present, meteorological data are received in near real time from the GTS network for different hours within one day. The data are pre-processed and quality checked using the AMDAC software package (MeteoConsult, 1991) which extracts, decodes and processes the GTS data.
Globally in the MARS DB are present data referred to more than 6000 stations distributed in 48 countries, but of these, only one third present an adequate level reliability and regularity providing data. In the table below are reported the number of meteorological stations by country used in operational way in the MCYFS.
In general, the meteo stations density in the monitored areas is sufficient for the purpose of the project. In the Fig. 2.2 it is shown which is in average the surface covered by one station. Considering that each cell of the CGMS-grid is 50x50 km (equivalent to 2.500 km2), is evident that the main agricultural areas present at least one station for each grid cell or one station for a group of four cells (equivalent to 10.000 Km2).
The data are collected from various sources:
- USA-NOAA (including METAR).
Observations of maximum and minimum temperatures, precipitation amounts and sunshine duration (when available) are contained in the main hours synoptic. METAR data provide temperature, dew point, visibility and cloud amount. As far as available, they can be used for intermediate or even non-standard (i.e. all but main and intermediate) hours. From most countries outside Europe, 3-hourly synoptic data are exchanged world wide and can be made available through Meteo Consult.
Data from outside the ECOMET area are transmitted from the Royal Netherlands Meteorological Institute (KNMI) as if WMO essential. A number of countries in Europe, especially in the east, are aiming to become a member of ECOMET. This might lead to a reduction in the amount of data freely available.
|Available number of meteorological stations by country|
Meteorological stations selected in priority are those located in the agricultural zones and equally distributed over the mainland (instead of over islands - for Portugal, Spain or Greece in particular). In particular, for western Russia (western of Urals) the main areas covered are the agricultural districts. Since 1 March 2004, a renewed station list has become operational. The most important changes are:
- For some countries (Austria, Belgium, Germany, Netherlands, Norway, Switzerland and United Kingdom) a fixed set of stations was used in the past. All available relevant station data from these countries are now sent to JRC. The reason for this is that sometimes stations are closed or the number of observed elements or observation hours is decreased. Increasing the total number of stations should ensure that the total required number is always reached.
- For countries where the aimed number of stations is or was not met, efforts have been undertaken to provide the maximum number available. Successful examples are Estonia, Spain, Turkey and Ukraine (see also below). The number for Morocco has also been increased.
- In the case of Spain, there are not enough synoptic stations to meet the aimed number. Data from additional stations were provided to meet the demand. However, these stations only report maximum and minimum temperature and precipitation amounts.
- For Turkey, additional station observations have become available through ECOMET. The JRC criteria are met by purchasing these data.
- In the case of Ukraine, many more stations have become available as a result of extensive negotiations which took a rather long period of time. The average number of available stations is now about 170. Moreover, observations are now present at 3-hourly time intervals.
- A special case is Portugal: the same set of stations is delivered as was usual during the last few years. However, we now only count the continental stations and not the island stations anymore. This results in a slight deficiency of stations for Portugal which cannot be solved, since there are no more stations at all.
- Improvements have not yet been achieved for Albania, Belarus, Latvia, Lithuania, Moldavia, Morocco (see above) and Romania. It isn’t possible to expect to meet the required number of stations for these countries on a short term. Either the station networks in these countries have been degraded or the National Weather Services are very difficult to contact or do business with.
Data quality check
For the data quality check a specific software named AMDAC has been developed. The software performs the following actions:
- Decode intermediate-hour and main-hour SYNOP reports and METAR reports from weather stations circulating on the GTS;
- Check the quality and correct the obvious errors in the received weather reports;
- Perform time consistency checks to compare the values of reported parameters with those previously or subsequently reported for the same station;
- Correct automatically obvious errors detected while performing consistency checks;
- Fill up automatically gaps in the database through interpolation based on time consistency criteria. This implies that observations from 18 UTC of the previous day until 12 UTC of the next day are available in order to compute an interpolation in time if missing values occurred;
- Flag errors and dubious observations and write these to a log file;
- Finally the data are converted into daily values. It comprises the selection of minimum and maximum temperature, the aggregation of the rainfall, cloud cover and sunshine duration, the calculation of mean vapor pressure etc.
The values of the following observation elements are checked: air temperature, dew-point temperature, pressure at sea level, wind speed, amount of precipitation, amount of clouds, duration of sunshine. Obvious errors in the observations are automatically corrected and a message is written to a log file. Dubious observations which can not automatically be corrected are also written to a log file. The operational meteorologist who has the possibility of modifying the data can read these latter messages. After the observations of a station are checked (and if necessary corrected) the derived parameters are recalculated and the data are written back to the database.
Once the database has been filled using the previous module, a final check is performed on the daily file before storing it in table METDATA. This automated quality check consists in verifying the following conditions:
|Daily mean of total cloud cover : N||0 to 8 octas|
|Measured sunshine duration: Msun||0 to 24 hours|
|Minimum temperature: Tn||-15 to 25°C|
|Maximum temperature: Tx||0 to 40°C|
|Maximum temperature - Minimum temperature||0< Tx-Tn <30°C|
|Daily mean vapor pressure: e||0 to 30 hPa|
|Daily mean wind speed at 10 metres: ff10||0 to 15 m/s|
|Amount of precipitation from 6 UTC-6 UTC: RRR||0 to 75 mm|
|Air temperature: TT||-15 to 40°C|
|Relative humidity: RH||20 to 100%|
|Daily mean vapor pressure deficit: vpd||0 to 40 hPa|
|Daily mean slope of saturation vapor pressure vs. temperature curve: slope||0 to 3 hPa/°C|
|Daytime mean of total cloud cover: N||0 to 8 octas|
|Penman evaporation: ETP||0 to 10 mm/day|