Difference between revisions of "Analysis of weather indicators"

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.

Marsop3 viewers

The Marsop3 viewers are developed to analyse the available datasets. The analyst version has full functionality and can access all datasets. The web version serves the 'outside' world with a selection of datasets and limited functionality. The data can be analysed in spatial (maps) and temporal resolution (graps). Data are available from 1975 onwards.

Extreme weather events that can be analysed in maps 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)
• 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 5mm, 10mm, 15mm)

Extreme weather events that can be analysed in 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

Quick-looks of ECMWF weather indicators

Besides creating on the fly maps of interpolated ECMWF weather using the Marsop3 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

Additional software

In order to permit the analysts to evaluate the possible influence of the meteorological conditions on the crops behavior in the best way additional simple software interfaces have been developed to analyse the data both in temporal and spatial resolution. The current interfaces are manly based on MS-Excel templates but in the close future, a new tool based on web technology will be available (Control board). The interfaces are connected directly to the database and permit to analyze the data both at station and at single grid cell level. The analysts (using a clickable map and defining the interested time length) can obtain graphs in which are shown the selected data and related simple statistical indicators (long-term average, standard deviation, cumulated values, absolute and relative differences, frequency, etc.). They also can have information on the extreme values presented in the database in relation to the period and station/grid selected.