Meteorological data from ECMWF models
General description
The ECMWF is one of the world's leading numerical modeling centres. It operates various global circulation models in various forecast depths. To evaluate the initial state of the atmosphere the models integrate observations from ground stations, radiosondes, satellites and many other sources. Special techniques bring these observations in balance with the meteorological equations to form a physically valid state of the atmosphere.
In order to extend the period of analysis and to better perform the crop monitoring and yield forecasting, weather forecasts are integrated in the MCYFS. These data permit to have important information on the evolution of the main meteorological phenomena at mesoscale.
The ECMWF's assimilation data is used to produce meteorological and derived agrometeorological parameters that are visualized in dynamic maps and graphs by the marsop3 viewer and static maps (quicklooks). Data from the ECMWF's Ensemble Prediction System (EPS), Monthly forecast model (MON) and Seasonal forecast model (SEA) have multiple forecast result. Small perturbations of the initial state are used to produce respectively 51, 50 and 50 different model runs.
Before ECMWF forecasted weather data can be ingested in the MCYFS, the data have to be preprocessed in order to get the appropriate resolutions in time and space.
Data acquisition from ECMWF
The data is delivered by ECMWF in FM92 GRIB format which is specified in WMO Publication 306 Manual on Codes. For the “Global Window” land and sea points are received. Filtering on land points takes place during decoding from GRIB format.
6 products of the ECMWF are ingested into the MCYFS:
Model  Abbreviation  Number of forecast days  Members  Gaussian grid*  Horizontal model resolution*  Acquired resolution**  Delivery 

ERAInterim****  ERA  1  1  N128  ~80km  0.75° x 0.75°  Once 
Analysis model  HIS  1  1  N640  ~16km  0.25° x 0.25°  Daily (10.30 hr) 
Deterministic forecast model  OPE  10  1  N640  ~16km  0.25° x 0.25°  Daily (12.00 hr) 
Ensemble Prediction System  EPS  15  51  N320 / N160***  ~30km / ~60km***  0.5° x 0.5°  Daily (14.00 hr) 
Monthly forecast model  MON  32  50  N320 / N160***  ~30km / ~60km***  0.5° x 0.5°  Every Friday (03.00 hr) 
Seasonal forecast model  SEA  183  50  N128  ~80km  1.5° x 1.5° / from 08/2013 onwards 0.75° x 0.75°  Every 8th of the month (14.00 hr) 
* resolution 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. Grid names start with 'N' followed by number of lines by which latitude is divided.
** resolution in which the simulated indicators are acquired and loaded into the MCYFS. The simulated indicators are distributed over the earth using a WGS84 coordinate system.
*** The first 10 days are simulated on a N320 grid (~30km horizontal resolution). The remaining days on a N160 grid (~60km horizontal resolution).
**** In more detail: ECWMF runs ERAInterim on IFS Version Cy31r1
ERAInterim is only used as archive containing daily data covering the period 19892010. From the HIS model only the forecast for the current day is processed (number of forecast days = 1) as best estimator for weather indicators of that day. The HIS data are stored as extension of the ERA_Interim archive. The data of other models are replaced when a more recent data set becomes available (OPE, EPS, MON and SEA). Therefore only the ERAInterim, extended with HIS data is used to calculate climatolgy.
For the OPE and EPS models the ECMWF model is run twice per day based on 00 and 12 UTC observations. As the delivery needs to take place until 15.00 hours of each day in standard situation the 00 UTC model run can be used. Sometimes, the model production is delayed so that a fallback to 12 UTC model data of the previous day will be taken into account.
Decoding and extraction of GRIB data
For the processing of the data it is needed to decode the data delivered in GRIB format. In previous years the program ‘wgrib’ has been used which is capable of extracting GRIB content into ASCII files for further processing. Recently ECMWF has released version 1.2.0 of their GRIB API which is the successor of GRIBEX. While GRIBEX was used within FORTRAN programs the new GRIB API is designed for programs written in the C programming language.
Abbreviations used in relation with ECMWF indicators  


During decoding additional indicators required by JRC and partners are calculated. This include aggregation to daily data, calculation of derived indicators and calculation of extreme weather events.
Aggregation to daily data
First of all an aggregation of 3, 6 and 12hourly data to daily data calculated. Algorithms for this have been developed within ASEMARS project and are different for the different ECMWF models. The algorithms are presented in the box below.
Algorithms for aggregation to daily data  

Abbreviations are specified in section Decoding and extraction of GRIB data. Subscript numbers behind the indicator abbreviations indicate the time of the day.
Aggregation areasTo consider the earth's different times zones aggregation rules for 3 different areas (East, Central, West) have been defined. The aggregation rules for the model data refer to the report schedule of synoptical weather stations (p.e. maximum air temperature in Europe and Africa refers to the period between 06 and 18 UTC of the corresponding day).
HISThe temporal resolution is 3hourly.
OPEThe temporal resolution is 3hourly until 72h and 6hourly afterwards. Algorithms for T2M, FFM and TD change at time step after FP +72.
ERA, EPS, MON and SEAThe temporal resolution is 6hourly.
* Only EPS model 
Calculation of advanced parameters
Not all indicators can be retrieved directly from the models. These include:
 Evapotranspiration
 Transpiration of water surface
 Transpiration of wet bare soil
 Climate water balance
 Vapour pressure
 Snow height
Evapotranspiration
In general, the evapotranspiration from a reference surface, the socalled reference crop evapotranspiration or reference evapotranspiration can be described by the FAO‑PenmanMonteith (Allen et all., 1998).
Evapotranspiration from a wet bare soil surface (ES0) and from a crop canopy (ET0) is calculated with the wellknown Penman formula (Penman, 1948). In general, the evapotranspiration from a water surface can be described by the Penman formula. Only the albedo and surface roughness differs for these two types of evapotranspiration as explained below.
The net absorbed radiation depends on incoming global radiation, net outgoing longwave radiation, the latent heat and the reflection coefficient of the considered surface (albedo). For ET0, ES0, and ET0 albedo values of 0.05, 0.15 and 0.20 are used respectively. The evaporative demand is determined by humidity, wind speed and surface roughness. For a free water surface and for the wet bare soil (E0, ES0) a surface roughness value of 0.5 is used. For a more detailed description of the underlying formulae we refer to Supit et al. (1994) and van der Goot (1997).
Climatic water balance
Climatic water balance is calculated based on evapotranspiration calculated through the equation of PenmanMonteith and the total precipitation of a day.
CWB equals Rain – ET0 

where:

Snow height
For visualisation in the new MARS viewer the snow height (thickness of the snow layer) is derived from snow depth (water equivalent) and snow density.
Dsn equals r_water/r_water * S/c_snow 

The ECMWF catalogue lists snow depth SD (water equivalent) for all sets and snow density RSN (kg/m3) which is available for OPE, ENS, MON but not for SEA. According to ECMWF documentation snow height Dsn can be derived with the approach
Dsn equals r_water/r_snow*S/c_snow with
In ECMWF's model documentation snow mass is (sometimes) referred as “snow water equivalent”, and leads to parameter SD, snow depth. Snow fraction is not in the catalogue. ECMWF assumes c_snow to be 1 for snow height > 15 cm (average of the grid box) and <1 for a thinner snow cover.

Calculation of extreme weather events
For the static map production over Europe it is necessary to derive additional parameters out of the raw data set. This especially concerns probabilities and aggregated counts of number of days where a special condition is met. Some of the probabilities to be mapped are available directly from ECMWF. Other probabilities need to be derived from individual ensemble runs. In this case it is checked for how many of the ensemble members a certain condition applies (e.g. TempMin < 0°C). The probability of the event is the fraction of ensemble members forecasting it against the total number of ensemble members. The operational run and the ensemble control run are treated like any other ensemble member.
Derived probability and other thresholddependent indicators  


Aggregation to 10daily and monthly data
After each 10day period and at the end of each month aggregation for this 10day/month period takes place. The daily data are aggregated from days to dekads by taking the average of mean temperature, maximum temperature, minimum temperature, snow depth and the sum of precipitation, ET0 and global radiation. For the 10daily/monthly processing it is necessary to add another aggregation level to produce 10daily/monthly sums and averages and to count the number of occurrences of certain events (such as frost, hot or rainy days).
Extraction of data into files and maps
The ECMWF models run on gaussian grids with different resolutions. The central MCYFS database however requires the initial data in a grid resolution with regular latitudes and longitudes. Therefore a conversion is needed. After conversion the data are exported as data files and static maps that can be distributed to users and other MCYFS processes.
The data files are loaded in the tables ECMWF_<MODEL>_DATA where <MODEL> is to be replaced by the abbreviation of one of the six ECMWF products (ERA, HIS, OPE, EPS, MON or SEA). These data are later to be used to create dynamic maps and graphs in the Marsop3 viewers.
The static maps are exported as flat images or animated images with full layout and directly made available to analysts that use them during analysis of weather indicators. The geographic extent of the static maps is defined by the upperleft corner at 75° North/25° West and the lowerright corner 20° North/70° East. This production line includes GrADS mapping software which is able to create maps directly from GRIB files. For the weekly and monthly maps the absolute difference to longterm average values are calculated.
Overview: Produced maps  


OPE & HIS
The Deterministic forecast model and Analysis model produce forecast weather for grid cells on a Gaussian N640 reduced grid (~16x~16km). The resolution is converted to a Gaussian N400 reduced grid (~25x~25km) and after this to a regular 0.25 x 0.25 degrees latitude longitude grid. In the near future a direct conversion from Gaussian N640 to the regular latitude, longitude grid is planned.
EPS & MON
The first 10 forecast days (Leg A) of the Ensemble Prediction System and Monthly forecast are modelled for grid cells on a Gaussian N320 reduced grid (~30x~30km). First the resolution is reduced to a Gaussian N200 reduced grid (~50x~50km) and finaly to a regular 0.5 x 0.5 degrees latitude longitude grid. In the near future a direct conversion from Gaussian N320 to the regular latitude, longitude grid is planned.
After the first 10 day, the resolution of the models for the remaining forecast days (LegB/C) is reduced to a Gaussian N160 reduced grid (~60x~60km). The results are directly converted into a regular 0.5 x 0.5 degrees latitude longitude grid.