Analysis of weather indicators

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Spatial analyses of average daily temperature, Difference between average over the year 2010 and long term average.
Temperal analyses of average daily temperature over the year 2010 in Italy.

To detect abnormal weather conditions, indicators are cumulated in time and compared with their equivalent long term average, previous year or any other year. This comparison shows if a specific period in the year of interest is more dry or wet, hot or cold etc. Extreme events such as excess of rainfall during sowing, flowering or harvest or prolonged droughts can be detected. Values can be cumulated over arbitrary periods.

MARSOP viewers

The MARSOP viewers are developed to analyse the available datasets. Data like temperature, rainfall, global radiation, evapotranspiration etc. can be analysed in spatial (maps) and temporal resolution (graps).

Some analysis can only be done at grid level as explained below.

Extreme weather events that can be analysed in maps (25 km climatic grid) and graphs:

  • temperature sum (above arbitrary base temperature)
  • number of heat waves over arbitrary period
  • longest heat wave over arbitrary period
  • number of hot days over arbitrary period (thresholds 25°C, 30°C, 35°C, 40°C)
  • number of cold days over arbitrary period (thresholds 0°C, -8°C, -10°C, -18°C, -20°C)
  • number of days with significant rain over arbitrary period (thresholds 1mm, 3mm, 5mm, 10mm, 15mm, 30mm)

Extreme weather events linked to crop development that can be analysed (in grid maps only):

  • number of heat waves around crop development stage
  • longest heat wave around crop development stage
  • rainfall around crop development stage
  • rainfall around sowing
  • temperature around crop development stage
  • temperature around sowing

Static maps (Quick-looks)

Animated Rainfall, emitted 20-dec-2010 with the forecasted precipitation of low "Petra". Petra's snow masses retarded travel in many regions of Europe before Christmas 2010. Large animation
Cloud coverage on 7-feb-2011.

Besides creating on the fly maps of interpolated ECMWF weather using the MARSOP viewers, the map production line delivers predefined quick-looks with full layout of the original model resolution and projection. This process is quicker than making the interpolated data available in the MARSOP3 viewer.

Overview of daily (OPE and EPS model) deliveries:

Parameter number of OPE maps number of EPS maps
Sea-level pressure 10+Animation 15+Animation
GPH 500 hPa 10+Animation 15+Animation
GPH 850 hPa 10+Animation 15+Animation
Tmin-24h 10+Animation 15+Animation
Tmax-24h 10+Animation 15+Animation
Tmean-24h 10+Animation 15+Animation
ΣRain-24h 10+Animation 15+Animation
ΣSnow-24h 10 15
ΣET0-24h 10 15
ΣCWB-24h 10 15
ΣRg-24h 10 15
Total Cloud Cover-24h 10 15
Prob Warm Anomaly +4 (850 hPa) - 15
Prob Warm Anomaly +8 (850 hPa) - 15
Prob Cold Anomaly -4 (850 hPa) - 15
Prob Cold Anomaly -8 (850 hPa) - 15
Prob Rain > 20mm - 15
Prob TempMin < 0 C - 15
Prob TempMax > 30 C - 15
ΣRain-10D 1 1
ΣSnow-10D 1 1
ΣET0-10D 1 1
ΣCWB -10D 1 1
Nr Rainy days (Rain > 1mm) 1 1
Nr Hot days (Tx > 30 C) 1 1
Nr Freezing days (Tn < 0 C) 1 1

Overview of weekly (MON model) and monthly (SEA model) deliveries:

Parameter number of MON maps number of MON lta maps number of SEA maps number of SEA lta maps
Tmin 4 4 4 4
Tmax 4 4 4 4
ΣRain 4 4 4 4
ΣSnow 4 4 4 4
ΣET0 4 4 4 4
ΣCWB 4 4 4 4
ΣRg 4 4 4 4
Probab. Warm Anomaly (+2K) 4 - 4 -
Probab. Cold Anomaly (-2K) 4 - 4 -
Probab. Of Rain > 10mm 4 - 4 -
Probab. Of Rain > 20mm 4 - 4 -
Probab. Temp <0°C 4 - 4 -
Probab. Temp >30°C 4 - 4 -
Nr. rainy days (Rain > 1mm) 4 4 4 4
Nr. hot days (TempMax > 30°C) 4 4 4 4
Nr. freezing days (TempMin < 0°C) 4 4 4 4