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Forecast Data

note

This Page provides information about the content of each individual forecast data package.

Further information can be found in the following places:

  • Specific package content can be found on this page. Please refer to the navigation on the right
  • Package output parameters can be found under API Output
  • Information about Weather Variables can be found on the Weather Variables page

General Packages

Basic

The basic package contains the most common weather variables. Despite the name, the basic package uses state of the art forecast technologies like mLM and nowcasting with real time corrections from nearby weather station and satellite and radar observations. Data are constantly updated to improve forecast quality.

Example URL: http://my.meteoblue.com/packages/basic-1h_basic-day?lat=47.558&lon=7.573&apikey=DEMOKEY

The basic package offers a 7 day forecast of precipitation, temperature, weather condition, wind speed & direction, humidity, sea level pressure, predictability and uv-index.

The 7 day weather forecast on the meteoblue website uses the basic package to display daily and 3-hourly data. Data on the website and in the API is identical.

Temperature

The temperature field is based on the mLM temperature forecast and is equivalent to a measurement 2 meters above ground. For complex terrain in the Alps and central Europe, meteoblue calculates specialized 700 m resolution domains to capture the precise local temperature. Thus changing the elevation can significantly change also the shape of the temperature curve, e.g. on a mountain peak, the diurnal variations seen in the valley can disappear almost completely. Outside Central Europe simpler elevation corrections are applied to account for the elevation difference between model topography and real topography. The elevation of the local topography at a given place is automatically determined using an 80m resolution digital elevation model, but it can also be specified manually with the &asl= URL parameter as described here.

If measurements from a nearby weather station are available, the temperature forecast is optimized for this station. Whether or not a station is used can be seen in the current package. Per default degree Celsius is used, but Fahrenheit can be selected with the temperature unit URL parameter.

The height of 2 meters above ground is most commonly used. Temperature forecasts for surface and in the soil are part of the agro package.

The 2 meter temperature might not represent the the perceived temperature. High humidity, strong winds and intense radiation increase or decrease the felt temperature. The felttemperature, tries to combine these factors.

For daily aggregations the minimum, mean and maximum is used. For 3 hourly values the values represents the reading at that point on time. It is not an average over 3 hours.

Precipitation

The precipitation field is the amount of all types of precipitation like rain, snow, ice, hail and convective showers. The field convective_precipitation only includes showers. Both fields must not be summed up. Precipitation is expressed as mm or inch depending on the precipitation amount unit parameter.

To calculate the amount of snow fall, the snowfraction field can be multiplied with the precipitation field. This snow fall amount in mm can be multiplied with 7 to get the equivalent snow depth. Example 1 mm precipitation is approximately equivalent to 7 mm snow fall. On some days there might be mixed conditions with rain and snow fall.

The precipitation in the basic package is calculated using multiple models with the meteoblue mLM technology. It is corrected using radar observations for the previous hours and the next 2 hours with a radar nowcasting. This correction applies to hourly data as well as daily aggregations.

For one and 3-hourly data, the precipitation value is the total amount of the preceding time-interval, similar to a rain gauge measurement. Example: For 3 hour data the precipitation at 12:00 is the sum of precipitation from 9:00 until 12:00. This is often misinterpreted by users. With 1-hourly precipitation this issue still exists, but is less noticeable.

To visualize the precipitation in the surroundings, the basic data package offers a rainspot to display rain in a 7x7 grid. Additional information is available here.

A more general description for precipitation amounts and probability can be found here.

rainSPOT

The rainSPOT represents the precipitation distribution around the chosen location. It is a 7x7 array encoded from south to north, west to east: 0000000000000011990009990000990000099000000000000

rainSPOT

0 = no rain, 1 = light rain (0.2 – 1.5 mm), 2 = medium (1.5 – 5 mm), 3 = heavy (>5 mm), 9 = shower (0.02 – 0.2 mm)

Please mind that the first digit in the API output represents the bottom left cell in the rainSPOT (see red 0 in the figure above).

Weather Condition Pictogram

To classify weather conditions "sunny", "partly cloudy" or "overcast with rain" the pictocode field uses a numeric number. It is very important to note, that hourly pictograms and daily pictograms use different numeric codes. The basic package uses hourly pictogram codes from 1-35 and daily pictogram code from 1-17.

The field isdaylight can be used to switch between daylight and night-time pictograms.

3-hourly Pictograms use the same numeric code as 1-hourly pictograms. 6-hourly pictograms use the same numeric code as daily pictograms. The 12:00 3h-hourly pictogram represents the weather conditions from 09:00 to 12:00. Additional information is available here.

Wind Speed and Direction

Wind speed forecasts are also based on mLM and should be equivalent to a measurement on 10 meters above ground. Winds closer to the ground are usually slower. To obtain wind speed at 2 meters, multiply the 10 m wind speed by a factor of 0.74, which gives a very good agreement on average. Per default kilometers per hour are used. A different unit can be selected with the wind speed unit URL parameter.

Wind speeds tend to fluctuate to a certain degree within one hour as well as within one grid-cell. The hourly wind speeds are an average over 1 hour and in one grid-cell. Wind gusts can therefore be significantly higher. The wind package provides wind speeds at 80 meters as well as wind gusts.

Wind forecasts may not capture the precise local wind conditions which are influenced by terrain, vegetation or buildings.

Wind direction is indicated in degrees (0° north, 90° east, 180° south, 270° west). It is the direction the wind is coming from. For daily aggregations the dominant wind direction is calculated which accounts for the wind speeds of each direction.

Additional information about wind is available here.

Predictability

A single weather forecasts model cannot be optimized for all weather conditions and areas. meteoblue operates a large number of weather models and collects data from multiple national weather services. Some models are more suitable for complex alpine terrain, while other models calculate fog conditions more precise. By combining multiple forecast models with statistics and machine learning algorithms, meteoblue calculates a learning multi-model forecasts (mLM). A byproduct of this approach is the ability to estimate the accuracy of the current forecast for each location.

If the majority of forecast models predicts the same weather conditions for a given location and achieve consensus, a high predictability is indicated. The predictability is given in percent, as well as a predictability_class which is just a simpler representation for the percentage value.

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
Precipitation*mm, inchWater amount1h, 3h, 6h, daySum
Precipitation probability%Likelihood of precipitation actually occurring1h, 3h, 6h, day
Precipitation hourshHours with precipitationday
Convective precipitation*mm, inchWater amount, caused by convection e.g. thunderstorms1h, 3h, 6h, daySum
Snow fraction0, 1information whether precipitation falls as rain or snow: 0 = rain, 1 = snow1h, 3h, 6h, dayAggregations: range from 0 till 1 (mean of hourly values)
Temperature°C, °F2m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Felt temperature°C, °F2m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max
Temperature instant°C, °FTemperature at 00:00 O'clockday
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end
Pictocode1 - 35, 1 - 171h & 3h: 1 - 35 day/night pictos, 6h & day: 1 - 17 iday pictos1h, 3h, 6h, day
Wind speedm/s, km/h, kn, mph, bf10m above ground5, 10, 15, 20, 30 mins,1h, 3h, 6h, dayMin, max, mean
Wind direction°, 2 char, 3 char10m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayDominant
Relative humidity%Air humidity5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
RH > 90%hday
Sea level pressurehPaAdjusted to mean sea level5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
rainSPOT0, 1, 2, 3, 90 ≤ 0.02 mm, 1 = 0.2 - 1.5 mm, 2 = 1.5 - 5 mm, 3 ≥ 5 mm, 9 = 0.02 - 0.2 mm1h, 3h, 6h, day
Predictability%24hday
Predictability class0 - 51 = very low, 5 = very highday
UV-index0 - 11+Ground levelday
Is-daylight0, 11 = day, 0 = night1h, 3h

*Precipitation is the total amount: Do not compute the sum of precipitation and convective precipitation.

Current

The Current data package contains current weather information, including observations and measurements. It returns current temperature, windspeed and condition measurement. It is not based on a single measurement, but combined from multiple weather stations using downscaling and interpolation algorithms. Current satellite and radar telemetry is used to adapt the weather condition pictogram. In case no weather station is nearby, a weather forecast model will be used.

Example URL: http://my.meteoblue.com/packages/current?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescription
Pictocode1 - 171 - 17, iday pictos (6h & day data)
Pictocode detailed1 - 351 - 35, day/night pictos (1h & 3h data)
Temperature°C, °F2m above ground, Temperature for indicated time
Wind speedm/s, km/h, kn, mph, bf10m above ground, Wind speed for indicated time
Is-daylight1 = day, 0 = night
Is-observation1 = obs available, 0 = no obs
Zenith angle°Angle between zenith and centre of the sun's disc
Metar IDIdentification Nr. of the Metar Station which provides the data

Clouds

The Clouds data package contains detailed cloud layer and sunshine duration forecasts.

Example URL: http://my.meteoblue.com/packages/clouds-1h_clouds-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
Low clouds%Cover of the sky5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Mid clouds%Cover of the sky5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
High clouds%Cover of the sky5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Total cloud cover%Cover of the sky5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
VisibilitymDistance5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Sunshine Timemin/hDirect sunlight, depends also on day length5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin/interval
Fog Probability%The likelihood of fog to occur in the defined time and area5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

Sun and Moon

The Sun and Moon data package contains information about rising and setting times of sun and moon. Rise and set times are indicated as string “hh:mm”. There are two special cases: If the moon does not rise and/or not set the field will have the value "---". If the moon is shining the entire day, then moonrise will be set to “00:00” and moonset will be “24:00”. The same applies if the sun does not rise and/or set, this time for the suns fields.

Example URL: http://my.meteoblue.com/packages/sunmoon?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Sunrise and sunset timehh:mmday
Moon rise and moon set timehh:mmday
Moon phase angledegreeday
Moon agedaysday
Moon phase namenameNew, waxing crescent, first quarter, waxing gibbous, full, waning gibbous, last quarter, waning crescentday
Moon phase transit timehh:mmday

Moonlight

The moonlight package contains parameters for assessing night sky conditions, providing information about the brightness of the sky under clear and actual conditions, the impact of moonlight, and the zenith angle.

Example URL: https://my.meteoblue.com/packages/moonlight-1h?lat=45&lon=5&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Moonlight clear sky%Percentage of light w.r.t. luminance of full moon at average distance not considering cloud-cover5, 10, 15, 20, 30 mins, 1h
Moonlight actual%Percentage of light w.r.t. luminance of full moon at average distance considering cloud-cover5, 10, 15, 20, 30 mins, 1h
Nightsky brightness clear skylxIlluminance of the nightsky in lux not considering cloud-cover5, 10, 15, 20, 30 mins, 1h
Nightsky brightness actuallxIlluminance of the nightsky in lux considering cloud-cover5, 10, 15, 20, 30 mins, 1h
Zenith angle°Solar zenith angle, important for twilight estimates5, 10, 15, 20, 30 mins, 1h

Web Colors

The Web Colors package contains the meteoblue HTML colour codes for web-formatting. For plotting numbers on the indicated colours, use the font-colour specified in the package.

Note: This package is only available in combination with a data package.

Example URL: http://my.meteoblue.com/packages/basic-day_webcolors?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnits
Temperature°C, °F
Felt temperature°C, °F
Wind speedm/s, km/h, kn, mph, bf
UV-Index1 - 11+
Predictability%

Agronomical Packages

Agro

The Agro data package serves agricultural purposes and contains soil and vegetation related weather variables.

Example URL: http://my.meteoblue.com/packages/agro-1h_agro-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
Skin / Surface temperature°C, °FSoil surface or skin1h, 3h, 6h, dayMin, max, mean
Wetbulb temperature°C, °F1h, 3h, 6h, dayMin, max, mean
Total evapotranspiration*mm1h, 3h, 6h, daySum
Potential evapotranspiration*mmAssuming unlimited water supply1h, 3h, 6h, daySum
Reference evapotranspiration* (ET_0)mm1h, 3h, 6h, daysum
Leaf wetness index0, 1Dew on leaves1h, 3h, 6h, dayMean
Soil temperature (0 - 10cm)°C, °F1h, 3h, 6h, dayMin, max, mean
Soil moisture (0 - 10cm)vol. %1h, 3h, 6h, dayMin, max, mean
Dew point temperature°C, °F2m above ground1h, 3h, 6h, dayMin, max, mean
Mean sensible heat fluxW/m2^2Mean energy flux of the surface energy balance which is used to heat(+) or cool(-) the air1h, 3h, 6h, dayMean
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

* For further information about the different evapotranspiration datasets, please consult the variable documentation.

Agromodel Leaf Wetness

The Agromodel Leaf Wetness data package contains all relevant information for monitoring and forecasting leaf wetness.

Example URL: http://my.meteoblue.com/packages/agromodelleafwetness-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Leaf wetness probability%Probability of leaf wetness (0% = low probability, 100% = high probability)1h
Leaf wetness rain index0 - 1Index describing the contribution of rain to leaf wetness (0 = no contribution, 1 = maximal contribution)1h
Leaf wetness dew index0 - 1Index describing the contribution of dew to leaf wetness (0 = no contribution, 1 = maximal contribution)1h
Leaf wetness evaporation index0 - 1Index describing the contribution of evaporation to leaf wetness (0 = no contribution, 1 = maximal contribution)1h

The indices have been designed to allow the professional user to calibrate each of the three elements influencing leaf wetness according to his local conditions, in order to compute a site specific leafwetness probability.

Agromodel Sowing

The Agromodel Sowing data package contains information about suitable time windows for sowing crops. Criteria used for sowing window:

  • Minimum soil temperature during (but not beyond) the forecast period (usually, a 5-7-day period), depending on crop; minimas for Maize and sunflower = 8°C.
  • Precipitation amount at and before the interval. Precipitation of more than 1 mm/hour will stop sowing for 12 hours after occurrence, or longer if evaporation rates are low.

The Agromodel Sowing data does not consider the following variables:

  • Suitable sowing season, as it does not consider previous precipitation, accumulated soil moisture in deeper levels and subsequent length of growing season. For these assessments, historic seasonal diagrams are necessary (e.g. history+).
  • Minimal soil moisture for germination, as this may vary substantially within few centimetres and by soil type, depends on the soil cover and planting method, and limit sowing periods unduly.

All variables use a recommendation classification from 0 to 2 (see below).

Example URL: http://my.meteoblue.com/packages/agromodelsowing-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnits*Intervals
Sowing maize0, 1, 21h
Sowing wheat0, 1, 21h
Sowing barley0, 1, 21h
Sowing rapseed0, 1, 21h
Sowing potato0, 1, 21h
Sowing sugarbeets0, 1, 21h
Sowing soybean0, 1, 21h
Sowing cotton0, 1, 21h
Sowing riceindica0, 1, 21h
Sowing ricejaponi0, 1, 21h
Sowing sorghum0, 1, 21h

Agromodel Spray

The Agromodel Spray data package contains information about suitable time windows for spraying fields.
The spraying conditions are calculated from the wind, precipitation, temperature and humidity forecasts. The recommendation must be verified just before the application with the current actual weather conditions.

All variables use a recommendation classification from 0 to 2 similar to the Agromodel Sowing package (see below).

Example URL: http://my.meteoblue.com/packages/agromodelspray-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnits*Intervals
Spray window0, 1, 21h

*Recommendation classifications:

ClassDescription
0Suitable period for application (green)
1Less suitable period for application (yellow)
2Unsuitable period for application (red)

Soil Trafficability

The Soil Trafficability data package contains information about the capacity of the soil to support moving vehicles based on the soil type and the development of water content in the top soil (0 - 10 cm).

Example URL: http://my.meteoblue.com/packages/soiltrafficability-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Sand0 - 1Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)1h
Silty Loam0 - 1Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)1h
Silt0 - 1Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)1h
Clay0 - 1Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)1h

Renewable Energy Packages

Solar

The Solar data package contains specific solar radiation variables for the solar energy sector.

Example URL: http://my.meteoblue.com/packages/solar-1h_solar-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
GHI (Solar radiation)W/m2^2Global horizontal radiation5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayInstant, Backwards (average of previous hour), Daily Sum
DIFW/m2^2Diffuse radiation5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayInstant, Backwards (average of previous hour), Daily Sum
DNIW/m2^2Direct normalized irradiance (Radiation)5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayInstant, Backwards (average of previous hour), Daily Sum
GNIW/m2^2Global normalized irradiance (Radiation)5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayInstant, Backwards (average of previous hour), Daily Sum
Extraterrestrial solar radiationW/m2^2Extraterrestrial solar radiation5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayInstant, Backwards (average of previous hour), Daily Sum

Solar Ensemble

The Solar Ensemble data package contains aggregated and individual members from the GFS ensemble solar forecasts. It consists of over 25 different forecasts and provides a long term estimate of expected conditions. meteoblue computes a most likely consensus forecast, the minimum and maximum, as well as the Percentiles exceedence values. The percentiles are computed directly from the data, not with any shortcuts assuming a gaussian distribution or standard deviations.

Example URL: http://my.meteoblue.com/packages/solarensemble-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

Variable GHIUnitsDescriptionIntervals
GHI backwards consensusW/m2^21h
GHI backwards p90 exceedenceW/m2^2Available as p95, p90, p85, p80, p75, p70, p60, p50, p40, p30, p25, p20, p15, p10, p51h
Max GHI backwardsW/m2^21h
Min GHI backwardsW/m2^21h

Example: The P90_exceedence for GHI gives the global horizontal irradiation which is exceeded with 90% probability and thus is obviously much smaller than e.g. a P30_exceedence GHI, which is only reached with 30% probability.

Note: The distributions and weather uncertainty in the forecasts are using real probabilistics and are therefore not gaussian.

PV Pro

The PV Pro data package contains solar power production forecasts based on kilowatt peak as well as panel inclination and orientation.

Example URL: http://my.meteoblue.com/packages/pvpro-1h_pvpro-day?lat=47.558&lon=7.573&kwp=1&slope=20&facing=180&power_efficiency=0.9&tracker=1&apikey=DEMOKEY

Required Input Parameters

NameDescriptionExampleDefault
kWpKilowatt peak production&kwp=1null
SlopeInclination of solar panel&slope=20null
FacingOrientation of solar panel&facing=180null
Power efficiencyPower efficiency of pv module&power_efficiency=0.90.85
Tracker*For solar panels using a sun tracker&tracker=1null

Package Content

VariableUnitsDescriptionIntervalsAggregations (day)
PV powerkWh, mW/hPhotovoltaic power5, 10 ,15, 20, 30 mins, 1h, dayInstant, Backwards (average of previous hour), Daily Sum
GTIW/m2^2Global Tilted Irradiance (Radiation)5, 10, 15, 20, 30 mins, 1h, dayInstant, Backwards (average of previous hour), Daily Sum
Performance ratio%5 ,6, 10, 15, 20, 30 mins, 1h
Module temperature°C, °F5 ,6, 10, 15, 20, 30 mins, 1h, dayInstant, Backwards (average of previous hour), Daily Mean
IAM%Incidence Angle Modifier5, 10, 15, 20, 30 mins, 1hInstant, Backwards (average of previous hour)
Snow covercmOn the PV modules, Considers inclination5, 10, 15, 20, 30 mins, 1h, dayMean
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

Package Specific Output Parameters

Output parametersUnitsDescription
Facing°Orientation of solar panel
kWpkWPeak capacity of solar system
Slope°Inclination of solar panel
Tracker*ModeFor solar panels using a sun tracker

*Sun Tracker Definition

ModeDescription
1Daily vertical axis tracker
2Daily 2-axis tracker
3Yearly horizontal tracker
4Daily DNI tracker
5Daily horizontal axis tracker

PV Ensemble

Example URL: https://my.meteoblue.com/packages/pvensemble-1h?lat=47.558&lon=7.573&kwp=1&slope=20&facing=180&power_efficiency=0.9&tracker=0&asl=279&tz=Europe%2FZurich&name=Basel&format=json&apikey=DEMOKEY

Required Input Parameters

NameDescriptionExampleDefault
kWpKilowatt peak production&kwp=1null
SlopeInclination of solar panel&slope=20null
FacingOrientation of solar panel&facing=180null
Power efficiencyPower efficiency of pv module&power_efficiency=0.90.85
Tracker*For solar panels using a sun tracker&tracker=1null

Package Content

VariableUnitsDescriptionIntervals
PV power backwards consensuskW1h
PV power backwards p90 exceedencekWAvailable as p95, p90, p85, p80, p75, p70, p60, p50, p40, p30, p25, p20, p15, p10, p51h
Max PV power backwardskW1h
Min PV power backwardskW1h

Package Specific Output Parameters

Output parametersUnitsDescription
Facing°Orientation of solar panel
kWpkWPeak capacity of solar system
Slope°Inclination of solar panel
Tracker*ModeFor solar panels using a sun tracker

*Sun Tracker Definition

ModeDescription
1Daily vertical axis tracker
2Daily 2-axis tracker
3Yearly horizontal tracker
4Daily DNI tracker
5Daily horizontal axis tracker

Wind

The Wind data package contains specific wind variables for the wind energy sector.

Example URL: http://my.meteoblue.com/packages/wind-1h_wind-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
Wind gustsm/s, km/h, kn, mph, bf10m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Wind direction 80m°, 2 char, 3 char80m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayDominant
Wind speed 80mm/s, km/h, kn, mph, bf80m above ground5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Air densitykg/m3^3As result of altitude, temperature and humidity5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean
Air pressurehPaAt surface height, not converted to sea level5, 10, 15, 20, 30 mins, 1h, 3h, 6h, dayMin, max, mean

Wind 80m Ensemble

The Wind 80m Ensemble data package contains aggregated and individual members from the GFS ensemble wind forecasts. It consists of over 25 different forecasts and provides a long term estimate of expected conditions. meteoblue computes a most likely consensus forecast, the minimum and maximum, as well as the percentiles exceedence values. The percentiles are computed directly from the data, not with any shortcuts assuming a gaussian distribution or standard deviations.

Example URL: http://my.meteoblue.com/packages/wind80ensemble-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

Variable GHIUnitsDescriptionIntervals
Wind speed 80m consensusm/s, km/h, kn, mph, bf80m above ground1h
Wind speed 80m p90 exceedencem/s, km/h, kn, mph, bfAvailable as p95, p90, p85, p80, p75, p70, p60, p50, p40, p30, p25, p20, p15, p10, p51h
Max wind speed 80mm/s, km/h, kn, mph, bf80m above ground1h
Min wind speed 80mm/s, km/h, kn, mph, bf80m above ground1h

Example: The P90_exceedence for wind speed gives the speed which is exceeded with 90% probability and thus is obviously much smaller than e.g. a P30_exceedence wind speed, which is only reached with 30% probability.

Note: The distributions and weather uncertainty in the forecasts are using real probabilistics and are therefore not gaussian.

Wind Power

The Wind Power data package contains wind power forecasts at a height of 80m.

Example URL: https://my.meteoblue.com/packages/windpower-1h?lat=47.558&lon=7.573&asl=279&turbineid=-1&kwp=1&power_efficiency=0.9&numberofturbines=5&tz=Europe%2FZurich&name=Basel&format=json&apikey=DEMOKEY

Required Input Parameters

NameDescriptionExampleDefault
Turbine IDTurbine type&turbineid=-1*null
Power efficiencyPower efficiency of wind turbine&power_efficiency=0.91
Number of turbinesNumber of turbines&numberofturbines=101
kWp**Kilowatt peak production&kwp=11

* You can find the list of the turbine IDs / types here.

** only applicable for standard turbine (turbineid=-1)

Package Content

VariableUnitsDescriptionIntervals
Wind PowerkW80m above ground5, 10, 15, 20, 30 mins, 1h

Package Specific Output Parameters

Output parametersUnitsDescription
Turbine TypeTypeSelected Turbine Type
kWpkWPeak capacity of wind turbine
Number of Turbines#Number of turbines
Forecast Type-RAW
Power efficiency%Power efficiency of wind turbine

Wind Power Ensemble

Example URL: https://my.meteoblue.com/packages/windpowerensemble-1h?lat=47.558&lon=7.573&asl=279&tz=Europe%2FZurich&name=Basel&format=json&turbineid=1&power_efficiency=0.9&numberofturbines=5&kwp=1&apikey=DEMOKEY

Required Input Parameters

NameDescriptionExampleDefault
Turbine IDTurbine type&turbineid=-1*null
Power efficiencyPower efficiency of wind turbine&power_efficiency=0.91
Number of turbinesNumber of turbines&numberofturbines=101
kWp**Kilowatt peak production&kwp=11

* You can find the list of the turbine IDs / types here.

** only applicable for standard turbine (turbineid=-1)

Package Content

VariableUnitsDescriptionIntervals
Wind PowerkW80m above ground1h

Package Specific Output Parameters

Output parametersUnitsDescription
Turbine TypeTypeSelected Turbine Type
kWpkWPeak capacity of wind turbine
Number of Turbines#Number of turbines
Forecast Type-RAW
Power efficiency%Power efficiency of wind turbine

Advanced Packages

Sea

The Sea data package contains marine weather forecasts. The forecasts are only valid for locations located at least 20km away from the coast. Note also that, as the predictability drops severely for forecasts further than 5 days ahead, data for future periods beyond that may not always be available.

Example URL: http://my.meteoblue.com/packages/sea-1h_sea-day?lat=67.552&lon=4.222&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
Significant wave heightmAverage of all waves, effective wave height (as would be observed, not average)1h, 3h, 6h, dayMin, max, mean
Wind wave direction°Average for open sea, direction to which the waves move1h, 3h, 6h, dayDominant
Sea surface temperature°C, °FAverage for (open) sea, mean1h, 3h, 6h, dayMean
Wind wave heightmHighest 3 of wind waves1h, 3h, 6h, dayMin, max, mean
Mean wind wave periodsMajority of waves1h, 3h, 6h, dayMin, max, mean
Mean wave direction°Average of all waves, direction to which the waves move1h, 3h, 6h, dayDominant
Mean wave periodsAverage of all waves1h, 3h, 6h, dayMin, max, mean
Significant height of swell wavesmHighest waves average1h, 3h, 6h, dayMin, max, mean
Mean period of swell wavessHighest waves average1h, 3h, 6h, dayMin, max, mean
Peak wave period of swell wavess1h, 3h, 6h, dayMin, max, mean
Peak wave period of wind wavess1h, 3h, 6h, dayMin, max, mean
Mean direction of swell waves°1h, 3h, 6h, dayDominant
Current velocity Um/sVelocity on longitude-axis1h, 3h, 6h, dayMin, max, mean
Current velocity Vm/sVelocity on latitude-axis1h, 3h, 6h, dayMin, max, mean
SalinityPSA**Practical salinity unit1h, 3h, 6h, dayMean
Douglas seastateClassification of sea conditions based on observed wave height1h, 3h, 6h, dayMin, max, mean
Surfwave heightm, ftVertical distance between the crest and trough of a wave in water1h, 3h, 6h, dayMin, max, mean
WavesteepnessRatio of wave's height to its wavelength1h, 3h, 6h, dayMin, max, mean
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

Air

The Air data package contains atmospheric forecasts like CAPE and lifted index.

Example URL: http://my.meteoblue.com/packages/air-1h_air-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (6h, day)
CAPEJ/kgConvective Available Potential Energy1h, 3h, 6h, dayMin, max, mean
Lifted indexJ/kgRisk of thunderstorms: Measure of atmospheric instability1h, 3h, 6h, dayMin, max, mean
Thunderstorm probability%Risk of thunderstorms: quantifies the chances of thunderstorm formation within a defined geographical area within a specified time frame1h, 3h, 6h, day
Boundary layer heightmLayer with inversion1h, 3h, 6h, dayMin, max, mean
Helicitym2^2s2^-2Potential for helical flow1h, 3h, 6h, dayMin, max, mean
Convective inhibitionmMeasure of the unlikelihood of thunderstorm development1h, 3h, 6h, dayMin, max, mean
Cloud icegTotal atmospheric column frozen water content of all clouds, excluding precipitation, Total column (ground to top of atmosphere)1h, 3h, 6h, dayMin, max, mean
Cloud watergTotal atmospheric column liquid water content of all clouds, excluding precipitation, Total column (ground to top of atmosphere)1h, 3h, 6h, dayMin, max, mean
Freezing level heightmZero-degree isotherm in the free atmosphere, above sea level1h, 3h, 6h, dayMin, max, mean
Windchill°C, °FCooling effect of wind on the human perception of temperature1h, 3h, 6h, dayMin, max, mean
Heatindex°C, °FAssessment of temperature perceived by human body due to combined effects of heat and humidity1h, 3h, 6h, dayMin, max, mean
Wet-bulb globe temperature°C, °FLowest temperature achievable through water evaporation1h, 3h, 6h, dayMin, max, mean
Convective cloud base pressurehPaAtmospheric pressure at cloud base of vertically developing clouds1h, 3h, 6h, dayMin, max, mean
Convective cloud top pressurehPaAtmospheric pressure at cloud top of vertically developing clouds1h, 3h, 6h, dayMin, max, mean
Convective updraft velocitym/sVelocity of rising air masses driven by convection1h, 3h, 6h, dayMin, max, mean
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

Air Quality

The Air Quality data package contains air quality forecasts like pollutant concentrations. Within Europe, the resolution of the forecast is 12 km, which is very high for air quality purposes, however the forecast cannot capture local effects like pollution along a road in a city, where actual concentrations could be much higher. In such a case you should refer to very local measurements taken at the exact spot of interest.

Example URL: http://my.meteoblue.com/packages/airquality-1h_airquality-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (day)
Ozone concentrationμg/m3^32m above ground1h, 3h, dayMin, max, mean
Dust concentrationμg/m3^32m above ground1h, 3h, dayMin, max, mean
PM2.5 concentrationμg/m3^32m above ground, particulate matter1h, 3h, dayMin, max, mean
PM10 concentrationμg/m3^32m above ground, particulate matter1h, 3h, dayMin, max, mean
SO2_2 concentrationμg/m3^32m above ground, sulphur dioxide1h, 3h, dayMin, max, mean
NO2_2 concentrationμg/m3^32m above ground, nitrogen dioxide1h, 3h, dayMin, max, mean
CO concentrationμg/m3^32m above ground, carbon monoxide1h, 3h, dayMin, max, mean
Birch pollenμg/m3^32m above ground, Europe only1h, 3h, dayMin, max, mean
Grass pollenμg/m3^32m above ground, Europe only1h, 3h, dayMin, max, mean
Olive pollenμg/m3^32m above ground, Europe only1h, 3h, dayMin, max, mean
AOD550 concentrationμg/m3^32m above ground, aerosol optical depth at 550 nm1h, 3h, dayMin, max, mean
Air quality index0-1002m above ground1h, 3h, dayMin, max, mean
Sandstorm alert0,12m above ground1h, 3h, day
Index to 1h valuesIndexCorresponding hourly Index to daily valuesdaystart, end

Sigma Level

The Sigma Level data package contains atmospheric layer forecasts above 300m.

Example URL: http://my.meteoblue.com/packages/sigmalevel-1h_sigmalevel-day?lat=47.558&lon=7.573&sigmalevel=1200&apikey=DEMOKEY

Required Input Parameters

NameDescriptionExampleDefault
Sigma levelHeight above ground in [m]&sigmalevel=1200null

Package Content

VariableUnitsDescriptionIntervalsAggregations (day)
Temperature°C, °F1h, 3h, dayMin, max, mean
Air densitykg/m3^3As result of altitude, temperature and humidity1h, 3h, dayMin, max, mean
Relative humidity%Air humidity1h, 3h, dayMin, max, mean
Wind speedm/s, km/h, kn, mph, bf1h, 3h, dayMin, max, mean
Wind direction°, 2 char, 3 char1h, 3h, dayDominant

Note: The Sigma Level package must not be used for heights less than 300m above ground, since such data would be heavily influenced by the surface. The highest available data layer is computed for 150mb (10 kilometers or more above ground).

Profile Series

Data for the following Profile Series are provided on different vertical levels. They are available in steps of 50mb for the pressure range of 150mb to 850mb, and steps of 25mb for the range of 850mb to 1000mb.

Profile Series Temperature

Example URL: http://my.meteoblue.com/packages/profiletemp-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Temperature profile°C, °F1h, 3h

Profile Series Geopotential Height

Example URL: http://my.meteoblue.com/packages/profileheight-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Geopotential height profilegpm1h, 3h

Profile Series Wind

Example URL: http://my.meteoblue.com/packages/profilewind-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Wind speed profilem/s, km/h, kn, mph, bf1h, 3h
Wind direction profile°, 2 char, 3 char1h, 3h

Profile Series Cloud Cover

Example URL: http://my.meteoblue.com/packages/profileclouds-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Cloud cover profile%Cover of the sky1h, 3h

Profile Series Relative Humidity

Example URL: http://my.meteoblue.com/packages/profilerh-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Relative humidity profile%Air humidity1h, 3h

Snow Ice

The Snow Ice package provides forecast data of "winter" precipitation types, snow and ice.

Example URL: https://my.meteoblue.com/packages/snowice-1h?lat=48&lon=8&asl=209&name=abcd&cache=no&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Freezingrainmm1h
Icing on surfacemm1h
Icing on wiremm1h
Precipitationtype 0mmNo Precipitation1h
Precipitationtype 1mmRain1h
Precipitationtype 2mmSnow1h
Precipitationtype 3mmRain Snow Mix1h
Precipitationtype 4mmSleet1h
Precipitationtype 5mmFreezing Rain1h
Precipitationtype 6mmFrozen Mix1h
Precipitationtype probability freezingrain%1h
Precipitationtype probability icepellets%1h
Precipitationtype probability rain%1h
Precipitationtype probability snow%1h
Snowaccumulationmm1h
Snowdepthm1h
Snowmeltmm1h

Ensemble and Probabilistic Forecasting Packages

Overview of Ensemble and Probabilistic Forecasting Data Packages:

trend-day1^1 , trend-1h2^2 , trendpro-day1^1multimodel-1h3^3ensemble-1h
Type of forecastConsensus or most likely forecast. Has downscaling and bias correctionsRaw model data from high resolu-tion modelsDownscaled, bias corrected en-semble members
Models usedEnsemble members, high resolution modelsHigh resolution modelsGFS-ensemble
Probabilistic informationSpread4^4, overall predictabilityIndividual highresolution modelsIndividual ensemble members and control forecast
Forecast horizon14 daysUp to 7 days14 days
Important restrictionsRaw model data, no bias correction or other improvements done to forecast. Variable number of models and forecast horizons depending on location and model. Not a true ensemble, thus some members might provide better forecast under certain weather conditions, depending on the location.Variability in the first 5 days not accurately captured, use multimodel if first 5 days are main focus. Accuracy for first 7 days not competitive with other packages. 1h data is for technical simplification only, there is no skill in 1h 14 day forecasts. Not available in CSV format.

If you are looking for the best possible 7 day forecast and are not interested in details about forecast uncertainties of different weather variables, none of these packages should be used.

To access the most accurate short-term forecast, do not use the multimodel or ensemble forecast data packages. The basic data package always uses the highest resolution model available for the selected location and is updated with local measurements and observational data (if available) and therefore, this data package is more suitable for short-term forecasts.

1^1The trend data packages deliver the same forecast data than in the standard data package for 7 forecast days (180 hours). For the remaining days (forecast days 8 – 14), you get trend data.

2^2The trend data packages deliver the same forecast data than in the standard data package for 7 forecast days (180 hours). For the remaining days (forecast days 8 – 14), you get trend data. 1h data is for technical simplification only, there is no skill in 1h 14 day forecasts.

3^3This raw model data is consistent with history-data. If you train your own AI-model based on history data, this is the package you need to use for forecasts.

4^4The spread - defined as 1 standard deviation (StD) from the mean of the different model predictions - may be used to roughly estimate a 95% confidence interval, by adding / subtracting twice the variable spread to the variable value.

Multimodel Packages

Package Specific Output Parameters (for all Multimodels)

Output parametersUnitsDescription
Grid point elevationmMeters above sea level of model specific grid center

Multimodel

The Multimodel data package contains raw model output for all models available for the selected location, without any post-processing, down-scaling or corrections.

Example URL: http://my.meteoblue.com/packages/multimodel-1h_multimodel-3h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervals
Temperature°C, °F1h, 3h
Wind speedkm/h, m/s, knots, bf, mph1h, 3h
Wind direction°, 2 char, 3 char1h, 3h
Precipitationmm, inchWater amount1h, 3h
Cloud cover%Cover of the sky1h, 3h
Temperature spread°C, °F1 StD from the multimodel mean1h, 3h
Wind speed spreadkm/h, m/s, knots, bf, mph1 StD from the multimodel mean1h, 3h
GHI (Shortwave radiation)W/m2^2Global horizontal radiation1h, 3h

Note: The number of models may change between locations and even days, depending on availability: There are no guarantees of delivery of any particular model or of the timing on the update of any particular model for a given place or day. Models may be removed in the future or others may be added.

No quality control of any kind is performed on third party models included in this package. The main purpose of using the multimodel package is to determine a degree of uncertainty from the different model outputs, to compare models, to derive algorithms for selecting the best fit data and to store data for documentation purposes.

Restriction: The Multimodel data package is not available in CSV format.

Single Variable Multimodel

The Single Variable Multimodel data packages contain hourly data from all available models for specific variables. A true multimodel package contains low and high resolution models (able to detect more local weather phenomenon), with some models delivering better forecasts than others, depending on location, variable and weather condition. It therefore can reproduce the uncertainities in the weather forcast for the next 3 to 5 days much better than an ensemble package, that tends to overestimate the confidence in the foreast.

When using the Single Variable Multimodel packages, make sure that your code can cope with the following:

  • at any time, without any prior notice, a model could disappear from the package (e.g. because some agency decides that a particular model will not be continued or data will not be shared anymore).
  • at any time, without any prior notice, a new model could be added to the package.

Note: Next to the raw data from all available models, these packages also deliver min, max, mean, stdv as well as p95- / p90- / … / p15- / p10-exceedence data.

Restriction: The single variable multimodel packages can not be combined with other hourly data packages in the same call.

Multimodel Temperature

Example URL: http://my.meteoblue.com/packages/multimodeltemperature-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Temperature°C, °F5, 10, 15, 20, 30 mins, 1h

Multimodel Precipitation

Example URL: http://my.meteoblue.com/packages/multimodelprecipitation-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Precipitationmm, inchWater amount5, 10, 15, 20, 30 mins, 1h

Multimodel Relative Humidity

Example URL: http://my.meteoblue.com/packages/multimodelrh-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Relative Humidity%Air humidity5, 10, 15, 20, 30 mins, 1h

Multimodel Wind Speed

Example URL: http://my.meteoblue.com/packages/multimodelwind-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Wind speedkm/h, m/s, knots, bf, mph5, 10, 15, 20, 30 mins, 1h

Multimodel Wind Speed 80m

Example URL: http://my.meteoblue.com/packages/multimodelwind80-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsIntervals
Wind speed (80m)km/h, m/s, knots, bf, mph5, 10, 15, 20, 30 mins, 1h

Multimodel Wind Direction

Example URL: http://my.meteoblue.com/packages/multimodelwinddirection-1h?lat=47.558&lon=7.573&asl=279&format=json&apikey=DEMOKEY

VariableUnitsIntervals
Wind direction°5, 10, 15, 20, 30 mins, 1h

Multimodel Wind Direction 80m

Example URL: http://my.meteoblue.com/packages/multimodelwinddirection80-1h?lat=47.558&lon=7.573&asl=279&format=json&apikey=DEMOKEY

VariableUnitsIntervals
Wind direction (80m)°5, 10, 15, 20, 30 mins, 1h

Multimodel Wind Power

Example URL: https://my.meteoblue.com/packages/multimodelwindpower-1h?lat=47.558&lon=7.573&asl=279&tz=Europe%2FZurich&name=Basel&format=json&turbineid=-1&power_efficiency=0.9&numberofturbines=5&kwp=1&apikey=DEMOKEY

Required Input Parameters
NameDescriptionExampleDefault
Turbine IDTurbine type&turbineid=-1*null
Power efficiencyPower efficiency of wind turbine&power_efficiency=0.91
Number of turbinesNumber of turbines&numberofturbines=101
kWp**Kilowatt peak production&kwp=11

* You can find the list of the turbine IDs / types here.

** only applicable for standard turbine (turbineid=-1)

Package Content
VariableUnitsIntervals
Wind powerkW5, 10, 15, 20, 30 mins, 1h

Multimodel Clouds

Example URL: http://my.meteoblue.com/packages/multimodelclouds-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Clouds%Cover of the sky5, 10, 15, 20, 30 mins, 1h

Multimodel Radiation

Example URL: http://my.meteoblue.com/packages/multimodelradiation-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

VariableUnitsDescriptionIntervals
Shortwave radiationW/m2^2Backwards average5, 10, 15, 20, 30 mins, 1h

Multimodel PV

Example URL:  http://my.meteoblue.com/packages/multimodelpv-1h?lat=47.558&lon=7.573&slope=20&kwp=1&facing=180&tracker=1&apikey=DEMOKEY

Required Input Parameters
NameDescriptionExampleDefault
kWpKilowatt peak production&kwp=1null
SlopeInclination of solar panel&slope=20null
FacingOrientation of solar panel&facing=180null
Power efficiencyPower efficiency of pv module&power_efficiency=0.90.85
Tracker*For solar panels using a sun tracker&tracker=1null
*Sun tracker definition
ModeDescription
1Daily-1-axis-tracker
22-axis-tracker
3Yearly-1-axis-tracker
4DNI-tracker
5Daily-1-axis-slope-tracker
Package Content
VariableUnitsDescriptionIntervals
PV powerkWh, mW/hPhotovoltaic power5, 10, 15, 20, 30 mins, 1h

14-Day Forecast Packages

For the following trend data packages, we guarantee weather forecast data for 14 days (336h). However, forecast data for 384h may be available and delivered. It therefore is suggested that the API automation is implemented with the required flexibility, if the full available extend of the forecast is to be used.

Ensemble

The Ensemble data package contains all individual members of the GFS ensemble forecast. Ensemble data are down-scaled and bias corrected to higher spatial resolution and to 1h temporal resolution. The 1h time resolution is provided to simplify automatic processing, but it has to be clearly noted that it is impossible to have skilful 14-day forecasts at 1h time resolution. The control member is the forecast based on the original analysis; the 20 members are the forecasts resulting from the perturbation of the initial conditions. There is no best member, every member has the same probability of being correct or wrong. This data package is intended for professional customers who are familiar with ensemble forecasting and want to derive their own risk analysis for 5 to 14 days into the future.

Example URL: http://my.meteoblue.com/packages/ensemble-1h?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsEnsemble
Temperature°C, °F2m above ground1hGFS, ECMWF
Skin / Surface temperature°C, °FSoil surface or skin1hGFS
Wind speedm/s, km/h, kn, mph, bf10m above ground1hGFS, ECMWF
Wind direction°, 2 char, 3 char10m above ground1hGFS, ECMWF
Wind gustsm/s, km/h, kn, mph, bf10m above ground1hGFS
Precipitationmm, inchWater amount1hGFS, ECMWF
Low clouds%Cover of the sky1hGFS
Mid clouds%Cover of the sky1hGFS
High clouds%Cover of the sky1hGFS
GHI (Solar radiation)W/m2^2Global horizontal radiation (backwards)1hGFS

Package Specific Output Parameters

Output parametersUnitsDescription
ECMWF ensemble members-List of the ensemble members and cntl = avrage over all of them
GFS ensemble members-List of the ensemble members and cntl = avrage over all of them

Restriction: The multimodel data-package is not available in CSV format.

Trend

The Trend package contains 14-day ensemble forecasts for the most common weather variables.

Example URL: http://my.meteoblue.com/packages/trend-1h_trend-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (day)
Temperature°C, °F2m above ground1h, dayMin, max, mean
Temperature spread°C, °F2m above ground, 1 StD from the mean temperature1h, day
Precipitationmm, inchWater amount1h, daySum
Precipitation spreadmm, inchWater amount, 1 StD from the mean precipitation1h, day
Precipitation probability%day
Predictability%day
Predictability class0 - 50 = very low, 5 = very highday
Wind speedm/s, km/h, kn, mph, bf10m above ground1h, dayMin, max, mean
Wind speed spreadm/s, km/h, kn, mph, bf10m above ground, 1 StD from the mean wind speed1h, day
Wind direction°, 2 char, 3 char10m above ground1h, dayDominant
Sea level pressurehPaCorrected for sea level1h, dayMin, max, mean
Relative humidity%Air humidity1h, dayMin, max, mean
Total cloud cover%Cover of the sky, Analogue to METAR 0 - 81h, dayMin, max, mean
Total cloud cover spread%Cover of the sky, 1 StD from the mean cloud cover1h, day
Snow fraction0, 1information whether precipitation falls as rain or snow: 0 = rain, 1 = snow1h, dayHourly: 0 or 1, aggregations: range from 0 till 1 (mean of hourly values)
Pictocode1 - 35, 1 - 171h: 1 - 35 day/night pictos, day: 1 - 17 iday pictos1h, day
GHI backwardsW/m2^2
Wh/m2^2
Global Horizontal Radiation1h, daySum
Extraterrestrial radiation backwardsW/m2^2
Wh/m2^2
Extraterrestrial solar radiation1h, daySum
Isdaylight0, 11 = day, 0 = night1h

Trend Pro

The Trend Pro data package contains 14-day ensemble forecasts for a large variety of weather variables. It offers additonal variables compared to the regular trend package.

Example URL: http://my.meteoblue.com/packages/trendpro-1h_trendpro-day?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnitsDescriptionIntervalsAggregations (day)
Temperature°C, °F2m above ground1h, dayMin, max, mean
Temperature spread°C, °F2m above ground, 1 StD from the mean temperature1h, day
Felttemperature°C, °F1h, dayMin, max, mean
Precipitationmm, inchWater amount1h, daySum
Precipitation spreadmm, inch1 StD from the mean precipitation1h, day
Precipitation probability%1h, day
Wind speedm/s, km/h, kn, mph, bf10m above ground1h, dayMin, max, mean
Wind speed spreadm/s, km/h, kn, mph, bf10m above ground, 1 StD from the mean wind speed1h, day
Gust windm/skm/h, kn, mph, bf10m above ground, 1 StD from the mean wind gust1h, day
Wind direction°, 2 char, 3 char10m above ground1h, dayDominant
Sea level pressurehPaCorrected for sea level1h, dayMin, max, mean
Relative humidity%Air humidity1h, dayMin, max, mean
Total evapotranspiration*mm, inch1h, daySum
Reference evapotranspiration* (ET_0)mm, inch1h, daySum
Total cloud cover%Cloud cover, Cover of the sky1h, dayMin, max, mean
Total cloud cover spread%Cover of the sky, 1 StD from the mean cloud cover1h, day
Snow fraction0, 1information whether precipitation falls as rain or snow: 0 = rain, 1 = snow1h, dayHourly: 0 or 1, aggregations: range from 0 till 1 (mean of hourly values)
Pictocode1 - 35, 1 - 171h: 1 - 35 day/night pictos, day: 1 - 17 iday pictos1h, day
Low clouds%Cloud cover, Cover of the sky1h, dayMin, max, mean
Mid clouds%Cloud cover, Cover of the sky1h, dayMin, max, mean
High clouds%Cloud cover, Cover of the sky1h, dayMin, max, mean
Sunshine timemin/hDirect sunlight, Depends also on day length1h, daymin/Interval
VisibilitykmDistance1h, dayMin, max, mean
Skin/ Surface temperature°C, °FSoil surface or skin1h, dayMin, max, mean
Dew point temperature°C, °F2m above ground1h, dayMin, max, mean
CAPE1h, day
Lifted index1h, day
Predictability%day
Predictability class0 - 50 = very low, 5 = very highday
GHI backwardsW/m2^2
Wh/m2^2
Global horizontal radiation1h, daySum
Extraterrestrial radiation backwardsW/m2^2
Wh/m2^2
Extraterrestrial solar radiation1h, daySum
Isdaylight0, 11 = day, 0 = night1h
UV Index0 - 11+Ground levelday
Lifted indexJ/kgRisk of thunderstorms: Measure of atmospheric instability1h, daymin

* For further information about the different evapotranspiration datasets, please consult the variable documentation.

Long Term Forecasts

Weekly Subseasonal Anomaly

The calibrated seasonal and subseasonal forecast package contains information for calibrated long-range forecasts in the subseasonal (i.e., weeks ahead) and seasonal (i.e., months and seasons ahead) for the next six months. Our long-range forecast partner, the World Climate Service, provides these forecasts.

The package contains forecasts from NOAA’s Climate Forecast System Version 2 (CFSv2) seasonal forecast model, the European Centre for Medium-Range Weather Forecasts SEAS5 seasonal forecast model, and a proprietary multi-model ensemble (MME).

The forecasts are probabilistic tercile forecasts of each variable. Tercile forecasts predict the likelihood of future conditions being in the upper 33.3%, the middle 33.3%, and the lower 33.3% of the observed condition distribution. These categories are below normal (B), normal (N), and above normal (A).

The forecasts have been calibrated to be reliable, meaning the forecast condition should occur with the frequency with which they are forecasted. In other words, an above-normal temperature forecast of 60% for two months ahead will occur 60% of the time it’s forecasted. Forecast reliability is achieved via a data-intensive process called calibration, in which the performance of many years of reforecast data from the same forecast model is analyzed.

Example URL: https://my.meteoblue.com/packages/subseasonalanomaly-weekly?lat=40.0&lon=-50.0153&asl=8&&apikey=DEMOKEY

Package Content

VariableUnits
coolingdegreedays_meananomalyCDD
coolingdegreedays_meananomaly_trendCDD
coolingdegreedays_probability_above_average%
coolingdegreedays_probability_above_average_trend%
coolingdegreedays_probability_below_average%
coolingdegreedays_probability_below_average_trend%
coolingdegreedays_probability_near_normal%
coolingdegreedays_probability_near_normal_trend%
geopotentialheight_500mb_meananomalym
geopotentialheight_500mb_meananomaly_trendm
geopotentialheight_500mb_probability_above_average%
geopotentialheight_500mb_probability_above_average_trend%
geopotentialheight_500mb_probability_below_average%
geopotentialheight_500mb_probability_below_average_trend%
geopotentialheight_500mb_probability_near_normal%
geopotentialheight_500mb_probability_near_normal_trend%
heatingdegreedays_meananomalyHDD
heatingdegreedays_meananomaly_trendHDD
heatingdegreedays_probability_above_average%
heatingdegreedays_probability_above_average_trend%
heatingdegreedays_probability_below_average%
heatingdegreedays_probability_below_average_trend%
heatingdegreedays_probability_near_normal%
heatingdegreedays_probability_near_normal_trend%
precipitation_probability_above_average%
precipitation_probability_below_average%
precipitation_probability_near_normal%
precipitationanomaly_percentage_from_normal%
sealevelpressure_meananomalyhPa
sealevelpressure_probability_above_average%
sealevelpressure_probability_below_average%
sealevelpressure_probability_near_normal%
shortwaveradiation_meananomalyW/m2
shortwaveradiation_probability_above_average%
shortwaveradiation_probability_below_average%
shortwaveradiation_probability_near_normal%
temperature_meananomaly
temperature_meananomaly_trend
temperature_probability_above_average%
temperature_probability_above_average_trend%
temperature_probability_below_average%
temperature_probability_below_average_trend%
temperature_probability_near_normal%
temperature_probability_near_normal_trend%
windspeed_meananomalym/s
windspeed_probability_above_average%
windspeed_probability_below_average%
windspeed_probability_near_normal%

Please refer to the following table for an explanation of the variable types:

ContentDescription
Probability below averageThe probability that the selected variable will be in the lower 33.3% of the observed distribution from 1991 to 2020.
Probability near normalThe probability that the selected variable will be in the middle 33.3% of the observed distribution from 1991 to 2020.
Probability above averageThe probability that the selected variable will be in the upper 33.3% of the observed distribution from 1991 to 2020.
Mean anomalyDeviation from the weekly mean
TrendThe 'trend' involves eliminating the observed temperature trend before calibrating the forecasts. By removing the trend, the signal of the forecast model is highlighted more clearly, distinct from the underlying temperature trends.

Seasonal Anomalies Forecast

The Season Anomalies Forecast package contains all relevant information for trend forecasts of seasonal anomalies for the next 6 months. This package contains monthly seasonal forecast anomalies from different models as well as a super-ensemble (SA-ENSEMBLE) created by meteoblue, which is a mean based on over 300 individual forecasts from different forecast centers and is more likely to be true than any single model.

The package also contains the mean climate reference from the seasonal ECMWF forecast, to which the according ECMWF seasonal anomalies may be applied to. Please be aware that the main purpose of the package is to forecast a rough trend, and that the difference in the climate references from the different models may be much larger than the individual or aggregated trends.

Example URL: http://my.meteoblue.com/packages/seasonalanomaly-monthly?lat=47.558&lon=7.573&apikey=DEMOKEY

Package Content

VariableUnits
Temperature°C, °F
Precipitationmm
Sea surface temperature°C, °F
Sea level pressurehPa
Snow depthm
Evapotranspirationmm
Dew point temperature°C, °F
Wind speedm/s, km/h, kn, mph, bf
Total cloud cover%

Notes:

  • Each model updates once a month. However, as the forecasts come from different centers, each model does so at a different time during the month. The initialization time of each model is shown in the modelrun_utc metadata.
  • Not all models provide forecasts for all variables.
  • If you implement this package be aware that more models or variables could be added in the future if they become available.

For further information about the various models see here.