Forecast Data

note

For further information, please consider the weather variable documentation.

note

For questions regarding the API v2 migration, please check our API v2 FAQ. This page contains all technical information about the new meteoblue API.

We aim to provide a seamless migration process to the new API version. The current API will be replaced with the new API on 2024-03-04 at 10:00 CET.

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

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.

List of all Variables in the Basic Package

Variable	Units	Description	Intervals	Aggregations (6h, day)
Precipitation*	mm, inch	Water amount	1h, 3h, 6h, day	Sum
Precipitation probability	%	Likelihood of precipitation actually occurring	1h, 3h, 6h, day
Precipitation hours	h	Hours with precipitation	day
Convective precipitation*	mm, inch	Water amount, caused by convection e.g. thunderstorms	1h, 3h, 6h, day	Sum
Snow fraction	0, 1	information whether precipitation falls as rain or snow: 0 = rain, 1 = snow	1h, 3h, 6h, day	Aggregations: range from 0 till 1 (mean of hourly values)
Temperature	°C, °F	2m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
Felt temperature	°C, °F	2m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max
Temperature instant	°C, °F	Temperature at 00:00 O'clock	day
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, end
Pictocode	1 - 35, 1 - 17	1h & 3h: 1 - 35 day/night pictos, 6h & day: 1 - 17 iday pictos	1h, 3h, 6h, day
Wind speed	m/s, km/h, kn, mph, bf	10m above ground	5, 6, 10, 15, 20, 30 mins,1h, 3h, 6h, day	Min, max, mean
Wind direction	°, 2 char, 3 char	10m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Dominant
Relative humidity	%	Air humidity	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
RH > 90%	h		day
Sea level pressure	hPa	Adjusted to mean sea level	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
rainSPOT	0, 1, 2, 3, 9	0 ≤ 0.02 mm, 1 = 0.2 - 1.5 mm, 2 = 1.5 - 5 mm, 3 ≥ 5 mm, 9 = 0.02 - 0.2 mm	1h, 3h, 6h, day
Predictability	%	24h	day
Predictability class	0 - 5	1 = very low, 5 = very high	day
UV-index	0 - 11+	Ground level	day
Is-daylight	0, 1	1 = day, 0 = night	1h, 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

Variable	Units	Description
Pictocode	1 - 17	1 - 17, iday pictos (6h & day data)
Pictocode detailed	1 - 35	1 - 35, day/night pictos (1h & 3h data)
Temperature	°C, °F	2m above ground, Temperature for indicated time
Wind speed	m/s, km/h, kn, mph, bf	10m above ground, Wind speed for indicated time
Is-daylight	1 = day, 0 = night
Is-observation	1 = obs available, 0 = no obs
Zenith angle	°	Angle between zenith and centre of the sun's disc
Metar ID		Identification Nr. of the Metar Station which provides the data

An example for a possible output is shown in Figure below:

{
	"metadata":
	{
		"name": "",
		"latitude": 47.56,
		"longitude": 7.57,
		"height": 279,
		"timezone_abbrevation": "CEST",
		"utc_timeoffset": 2.00,
		"modelrun_utc": "2019-08-20 00:00",
		"modelrun_updatetime_utc": "2019-08-20 07:22"
	},
	"units":
	{
		"time": "YYYY-MM-DD hh:mm",
		"temperature": "C",
		"windspeed": "ms-1"
	},
	"data_current":
	{
		"pictocode": 6,
		"time": "2019-08-20 15:05",
		"temperature": 14.90,
		"isdaylight": 1,
		"windspeed": 1.19,
		"isobserveddata": 1,
		"zenithangle": 40.80,
		"pictocode_detailed": 23
	}
}

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

Variable	Units	Description	Intervals	Aggregations (6h, day)
Low clouds	%	Cover of the sky	1h, 3h, 6h, day	Min, max, mean
Mid clouds	%	Cover of the sky	1h, 3h, 6h, day	Min, max, mean
High clouds	%	Cover of the sky	1h, 3h, 6h, day	Min, max, mean
Total cloud cover	%	Cover of the sky	1h, 3h, 6h, day	Min, max, mean
Visibility	m	Distance	1h, 3h, 6h, day	Min, max, mean
Sunshine Time	min/h	Direct sunlight, depends also on day length	1h, 3h, 6h, day	Min/interval
Fog Probability	%	The likelihood of fog to occur in the defined time and area	1h, 3h, 6h, day	Min, max, mean
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, end

Sun and Moon

The Sun and Moon data package contains information about rising and setting times of sun and moon.

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

Variable	Units	Description	Intervals
Sunrise and sunset time	hh:mm		day
Moon rise and moon set time	hh:mm		day
Moon phase angle	degree		day
Moon age	days		day
Moon phase name	name	New, waxing crescent, first quarter, waxing gibbous, full, waning gibbous, last quarter, waning crescent	day
Moon phase transit time	hh:mm		day

An example for a possible output is shown in Figure below

"data_day": {
	"time": ["2019-05-14", "2019-05-15", ...],
	"sunrise": ["05:52", "05:50", ...],
	"sunset": ["20:59", "21:00", ...],
	"moonrise": ["15:33", "16:50", ...],
	"moonset": ["04:08", "04:35", ...],
	"moonphaseangle": [122.50, 135.70, ...],
	"moonage": [10.05, 11.13, ...],
	"moonphasename": ["waxing gibbous", "waxing gibbous", ...]
}

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.

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

Variable	Units
Temperature	°C, °F
Felt temperature	°C, °F
Wind speed	m/s, km/h, kn, mph, bf
UV-Index	1 - 11+
Predictability	%

An example for a possible output is shown in the following figure:

"data-day": {
	"temperature_max_color": ["#FCAC05", "#F88D00", ...], 
	"temperature_max_fontcolor": ["#000000", "#000000", ...], 
	"temperature_min_color": ["#B5FF33", "#B5FF33", ...], 
	"temperature_min_fontcolor": ["#000000", "#000000", ...], 
	"temperature_mean_color": ["#F8DF0B", "#F8DF0B", ...], 
	"temperature_mean_fontcolor": ["#000000", "#000000", ...], 
	"felttemperature_max_color": ["#F88D00", "#FC4F00", ...], 
	"felttemperature_max_fontcolor": ["#000000", "#000000", ...], 
	"felttemperature_min_color": ["#D8F7A1", "#D8F7A1", ...], 
	"felttemperature_min_fontcolor": ["#000000", "#000000", ...], 
	"predictability_class_color": ["#a0ce00", "#4eb400", ...], 
	"windspeed_max_color": ["#F8F8F8", "#F8F8F8", ...], 
	"windspeed_mean_color": ["#F8F8F8", "#F8F8F8", ...], 
	"windspeed_min_color": ["#F8F8F8", "#F8F8F8", ...]
}

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

Variable	Units	Description	Intervals	Aggregations (6h, day)
Skin / Surface temperature	°C, °F	Soil surface or skin	1h, 3h, 6h, day	Min, max, mean
Wetbulb temperature	°C, °F		1h, 3h, 6h, day	Min, max, mean
Total evapotranspiration*	mm		1h, 3h, 6h, day	Sum
Potential evapotranspiration*	mm	Assuming unlimited water supply	1h, 3h, 6h, day	Sum
Reference evapotranspiration* (ET_0)	mm		1h, 3h, 6h, day	sum
Leaf wetness index	0, 1	Dew on leaves	1h, 3h, 6h, day	Mean
Soil temperature (0 - 10cm)	°C, °F		1h, 3h, 6h, day	Min, max, mean
Soil moisture (0 - 10cm)	vol. %		1h, 3h, 6h, day	Min, max, mean
Dewpoint temperature	°C, °F	2m above ground	1h, 3h, 6h, day	Min, max, mean
Mean sensible heat flux	W/m$^2$	Mean energy flux of the surface energy balance which is used to heat(+) or cool(-) the air	1h, 3h, 6h, day	Mean
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, 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

Variable	Units	Description	Intervals
Leaf wetness probability	%	Probability of leaf wetness (0% = low probability, 100% = high probability)	1h
Leaf wetness rain index	0 - 1	Index describing the contribution of rain to leaf wetness (0 = no contribution, 1 = maximal contribution)	1h
Leaf wetness dew index	0 - 1	Index describing the contribution of dew to leaf wetness (0 = no contribution, 1 = maximal contribution)	1h
Leaf wetness evaporation index	0 - 1	Index 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.

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

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 which is defined below.

Variable	Units	Intervals
Sowing maize	0, 1, 2	1h
Sowing wheat	0, 1, 2	1h
Sowing barley	0, 1, 2	1h
Sowing rapseed	0, 1, 2	1h
Sowing potato	0, 1, 2	1h
Sowing sugarbeets	0, 1, 2	1h
Sowing soybean	0, 1, 2	1h
Sowing cotton	0, 1, 2	1h
Sowing riceindica	0, 1, 2	1h
Sowing ricejaponi	0, 1, 2	1h
Sowing sorghum	0, 1, 2	1h

Recommendation classifications

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

Agromodel Spray

The Agromodel Spray data package contains information about suitable time windows for spraying fields.

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

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 above).

Variable	Units	Intervals
Spray window	0, 1, 2	1h

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

Variable	Units	Description	Intervals
Sand	0 - 1	Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)	1h
Silty Loam	0 - 1	Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)	1h
Silt	0 - 1	Stability of the soil for moving vehicles (0 = no trafficability, 1 = good trafficability)	1h
Clay	0 - 1	Stability 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

Variable	Units	Description	Intervals	Aggregations (6h, day)
GHI (Solar radiation)	W/m$^2$	Global horizontal radiation	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Instant, Backwards (average of previous hour), Daily Sum
DIF	W/m$^2$	Diffuse radiation	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Instant, Backwards (average of previous hour), Daily Sum
DNI	W/m$^2$	Direct normalized irradiance (Radiation)	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Instant, Backwards (average of previous hour), Daily Sum
GNI	W/m$^2$	Global normalized irradiance (Radiation)	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Instant, Backwards (average of previous hour), Daily Sum
Extraterrestrial solar radiation	W/m$^2$	Extraterrestrial solar radiation	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Instant, 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

Variable GHI	Units	Description	Intervals
GHI backwards consensus	W/m$^2$		1h
GHI backwards p90 exceedence	W/m$^2$	Available as p95, p90, p85, p80, p75, p70, p60, p50, p40, p30, p25, p20, p15, p10, p5	1h
Max GHI backwards	W/m$^2$		1h
Min GHI backwards	W/m$^2$		1h

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

Variable	Units	Description	Intervals	Aggregations (day)
PV power	kWh, mW/h	Photovoltaic power	5, 6, 10 ,15, 20, 30 mins, 1h, day	Instant, Backwards (average of previous hour), Daily Sum
GTI	W/m$^2$	Global Tilted Irradiance (Radiation)	5, 6, 10, 15, 20, 30 mins, 1h, day	Instant, Backwards (average of previous hour), Daily Sum
Performance ratio	%		5 ,6, 10, 15, 20, 30 mins, 1h
Module temperature	°C, °F		5 ,6, 10, 15, 20, 30 mins, 1h, day	Instant, Backwards (average of previous hour), Daily Mean
IAM	%	Incidence Angle Modifier	5, 6, 10, 15, 20, 30 mins, 1h	Instant, Backwards (average of previous hour)
Snow cover	cm	On the PV modules, Considers inclination	5, 6, 10, 15, 20, 30 mins, 1h, day	Mean
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, end

Special Parameters:

Name	Description	Example	Default
Kwp	Kilowatt peak production	&kwp=1	Null
Slope	Inclination of solar panel	&slope=20	Null
Facing	Orientation of solar panel	&facing=180	Null
Power efficiency	Power efficiency of pv module	&power_efficiency=0.9	0.85
Tracker	For solar panels using a sun tracker*	&tracker=1	Null

Sun Tracker Definition:

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

Variable	Units	Description	Intervals	Aggregations (6h, day)
Wind gusts	m/s, km/h, kn, mph, bf	10m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
Wind direction 80m	°, 2 char, 3 char	80m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Dominant
Wind speed 80m	m/s, km/h, kn, mph, bf	80m above ground	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
Air density	kg/m$^3$	As result of altitude, temperature and humidity	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, max, mean
Air pressure	hPa	At surface height, not converted to sea level	5, 6, 10, 15, 20, 30 mins, 1h, 3h, 6h, day	Min, 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

Variable GHI	Units	Description	Intervals
Wind speed 80m consensus	m/s, km/h, kn, mph, bf	80m above ground	1h
Wind speed 80m p90 exceedence	m/s, km/h, kn, mph, bf	Available as p95, p90, p85, p80, p75, p70, p60, p50, p40, p30, p25, p20, p15, p10, p5	1h
Max wind speed 80m	m/s, km/h, kn, mph, bf	80m above ground	1h
Min wind speed 80m	m/s, km/h, kn, mph, bf	80m above ground	1h

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: http://my.meteoblue.com/packages/windpower-1h?lat=47.558&lon=7.573&turbineid=-1&kwp=10&apikey=DEMOKEY

Variable	Units	Description	Intervals
Wind Power	kW	80m above ground	5, 6, 10 ,15, 20, 30 mins, 1h

Special Parameters:

Name	Description	Example	Default
Turbine ID	Turbine type	&turbineid=-1*	Mandatory parameter
Power efficiency	Power efficiency of wind turbine	&power_efficiency=0.9	1
Number of turbines	Number of turbines	&numberofturbines=10	1
Kwp**	Kilowatt peak production	&kwp=1	1

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

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

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

Variable	Units	Description	Intervals	Aggregations (6h, day)
Significant wave height	m	Average of all waves, effective wave height (as would be observed, not average)	1h, 3h, 6h, day	Min, max, mean
Wind wave direction	°	Average for open sea, direction to which the waves move	1h, 3h, 6h, day	Dominant
Sea surface temperature	°C, °F	Average for (open) sea, mean	1h, 3h, 6h, day	Mean
Wind wave height	m	Highest 3 of wind waves	1h, 3h, 6h, day	Min, max, mean
Mean wind wave period	s	Majority of waves	1h, 3h, 6h, day	Min, max, mean
Mean wave direction	°	Average of all waves, direction to which the waves move	1h, 3h, 6h, day	Dominant
Mean wave period	s	Average of all waves	1h, 3h, 6h, day	Min, max, mean
Significant height of swell waves	m	Highest waves average	1h, 3h, 6h, day	Min, max, mean
Mean period of swell waves	s	Highest waves average	1h, 3h, 6h, day	Min, max, mean
Peak wave period of swell waves	s		1h, 3h, 6h, day	Min, max, mean
Peak wave period of wind waves	s		1h, 3h, 6h, day	Min, max, mean
Mean direction of swell waves	°		1h, 3h, 6h, day	Dominant
Current velocity U	m/s	Velocity on longitude-axis	1h, 3h, 6h, day	Min, max, mean
Current velocity V	m/s	Velocity on latitude-axis	1h, 3h, 6h, day	Min, max, mean
Salinity	PSA*	*Practical salinity unit	1h, 3h, 6h, day	Mean
Douglas seastate		Classification of sea conditions based on observed wave height	1h, 3h, 6h, day	Min, max, mean
Surfwave height	m, ft	Vertical distance between the crest and trough of a wave in water	1h, 3h, 6h, day	Min, max, mean
Wavesteepness		Ratio of wave's height to its wavelength	1h, 3h, 6h, day	Min, max, mean
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, 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

Variable	Units	Description	Intervals	Aggregations (6h, day)
CAPE	J/kg	Convective Available Potential Energy	1h, 3h, 6h, day	Min, max, mean
Lifted index	J/kg	Risk of thunderstorms: Measure of atmospheric instability	1h, 3h, 6h, day	Min, max, mean
Thunderstorm probability	%	Risk of thunderstorms: quantifies the chances of thunderstorm formation within a defined geographical area within a specified time frame	1h, 3h, 6h, day
Boundary layer height	m	Layer with inversion	1h, 3h, 6h, day	Min, max, mean
Helicity	m$^2$s$^-2$	Potential for helical flow	1h, 3h, 6h, day	Min, max, mean
Convective inhibition	m	Measure of the unlikelihood of thunderstorm development	1h, 3h, 6h, day	Min, max, mean
Cloud ice	g	Total atmospheric column frozen water content of all clouds, excluding precipitation, Total column (ground to top of atmosphere)	1h, 3h, 6h, day	Min, max, mean
Cloud water	g	Total atmospheric column liquid water content of all clouds, excluding precipitation, Total column (ground to top of atmosphere)	1h, 3h, 6h, day	Min, max, mean
Freezing level height	m	Zero-degree isotherm in the free atmosphere, above sea level	1h, 3h, 6h, day	Min, max, mean
Windchill	°C, °F	Cooling effect of wind on the human perception of temperature	1h, 3h, 6h, day	Min, max, mean
Heatindex	°C, °F	Assessment of temperature perceived by human body due to combined effects of heat and humidity	1h, 3h, 6h, day	Min, max, mean
Wet-bulb globe temperature	°C, °F	Lowest temperature achievable through water evaporation	1h, 3h, 6h, day	Min, max, mean
Convective cloud base pressure	hPa	Atmospheric pressure at cloud base of vertically developing clouds	1h, 3h, 6h, day	Min, max, mean
Convective cloud top pressure	hPa	Atmospheric pressure at cloud top of vertically developing clouds	1h, 3h, 6h, day	Min, max, mean
Convective updraft velocity	m/s	Velocity of rising air masses driven by convection	1h, 3h, 6h, day	Min, max, mean
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, 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

Variable	Units	Description	Intervals	Aggregations (day)
Ozone concentration	μg/m$^3$	2m above ground	1h, 3h, day	Min, max, mean
Dust concentration	μg/m$^3$	2m above ground	1h, 3h, day	Min, max, mean
PM2.5 concentration	μg/m$^3$	2m above ground, particulate matter	1h, 3h, day	Min, max, mean
PM10 concentration	μg/m$^3$	2m above ground, particulate matter	1h, 3h, day	Min, max, mean
SO$_2$ concentration	μg/m$^3$	2m above ground, sulphur dioxide	1h, 3h, day	Min, max, mean
NO$_2$ concentration	μg/m$^3$	2m above ground, nitrogen dioxide	1h, 3h, day	Min, max, mean
CO concentration	μg/m$^3$	2m above ground, carbon monoxide	1h, 3h, day	Min, max, mean
Birch pollen	μg/m$^3$	2m above ground, Europe only	1h, 3h, day	Min, max, mean
Grass pollen	μg/m$^3$	2m above ground, Europe only	1h, 3h, day	Min, max, mean
Olive pollen	μg/m$^3$	2m above ground, Europe only	1h, 3h, day	Min, max, mean
AOD550 concentration	μg/m$^3$	2m above ground, aerosol optical depth at 550 nm	1h, 3h, day	Min, max, mean
Air quality index	0-100	2m above ground	1h, 3h, day	Min, max, mean
Sandstorm alert	0,1	2m above ground	1h, 3h, day
Index to 1h values	Index	Corresponding hourly Index to daily values	day	start, 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

Variable	Units	Description	Intervals	Aggregations (day)
Temperature	°C, °F		1h, 3h, day	Min, max, mean
Air density	kg/m$^3$	As result of altitude, temperature and humidity	1h, 3h, day	Min, max, mean
Relative humidity	%	Air humidity	1h, 3h, day	Min, max, mean
Wind speed	m/s, km/h, kn, mph, bf		1h, 3h, day	Min, max, mean
Wind direction	°, 2 char, 3 char		1h, 3h, day	Dominant

Special Parameters:

Name	Description	Example	Default
Sigma level	Height above ground in [m]	&sigmalevel=1200	Mandatory parameter

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

Variable	Units	Intervals
Temperature profile	°C, °F	1h, 3h

Profile Series Geopotential Height

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

Variable	Units	Intervals
Geopotential height profile	gpm	1h, 3h

Profile Series Wind

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

Variable	Units	Intervals
Wind speed profile	m/s, km/h, kn, mph, bf	1h, 3h
Wind direction profile	°, 2 char, 3 char	1h, 3h

Profile Series Cloud Cover

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

Variable	Units	Description	Intervals
Cloud cover profile	%	Cover of the sky	1h, 3h

Profile Series Relative Humidity

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

Variable	Units	Description	Intervals
Relative humidity profile	%	Air humidity	1h, 3h

Snow ice

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

Variable	Units	Description	Intervals
Freezingrain	mm		1h
Icing on surface	mm		1h
Icing on wire	mm		1h
Precipitationtype 0	mm	No Precipitation	1h
Precipitationtype 1	mm	Rain	1h
Precipitationtype 2	mm	Snow	1h
Precipitationtype 3	mm	Rain Snow Mix	1h
Precipitationtype 4	mm	Sleet	1h
Precipitationtype 5	mm	Freezing Rain	1h
Precipitationtype 6	mm	Frozen Mix	1h
Precipitationtype probability freezingrain	%		1h
Precipitationtype probability icepellets	%		1h
Precipitationtype probability rain	%		1h
Precipitationtype probability snow	%		1h
Snowaccumulation	mm		1h
Snowdepth	m		1h
Snowmelt	mm		1h

Ensemble and Probabilistic Forecasting Packages

Overview of Ensemble and Probabilistic Forecasting Data Packages:

	trend-day$^1$ , trend-1h$^2$ , trendpro-day$^1$	multimodel-1h$^3$	ensemble-1h
Type of forecast	Consensus or most likely forecast. Has downscaling and bias corrections	Raw model data from high resolu-tion models	Downscaled, bias corrected en-semble members
Models used	Ensemble members, high resolution models	High resolution models	GFS-ensemble
Probabilistic information	Spread$^4$, overall predictability	Individual highresolution models	Individual ensemble members and control forecast
Forecast horizon	14 days	Up to 7 days	14 days
Important restrictions		Raw 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.

$^1$The 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.

$^2$The 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.

$^3$This 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.

$^4$The 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

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.

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.

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

Variable	Units	Description	Intervals
Temperature	°C, °F		1h, 3h
Wind speed	km/h, m/s, knots, bf, mph		1h, 3h
Wind direction	°, 2 char, 3 char		1h, 3h
Precipitation	mm, inch	Water amount	1h, 3h
Cloud cover	%	Cover of the sky	1h, 3h
Temperature spread	°C, °F	1 StD from the multimodel mean	1h, 3h
Wind speed spread	km/h, m/s, knots, bf, mph	1 StD from the multimodel mean	1h, 3h
GHI (Shortwave radiation)	W/m$^2$	Global horizontal radiation	1h, 3h

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

Variable	Units	Intervals
Temperature	°C, °F	1h

Multimodel Precipitation

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

Variable	Units	Description	Intervals
Precipitation	mm, inch	Water amount	1h

Multimodel Relative Humidity

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

Variable	Units	Description	Intervals
Relative Humidity	%	Air humidity	1h

Multimodel Wind Speed

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

Variable	Units	Intervals
Wind speed	km/h, m/s, knots, bf, mph	1h

Multimodel Wind Speed 80m

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

Variable	Units	Intervals
Wind speed (80m)	km/h, m/s, knots, bf, mph	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

Variable	Units	Intervals
Wind direction	°	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

Variable	Units	Intervals
Wind direction (80m)	°	1h

Multimodel Clouds

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

Variable	Units	Description	Intervals
Clouds	%	Cover of the sky	1h

Multimodel Radiation

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

Variable	Units	Description	Intervals
Shortwave radiation	W/m$^2$	Backwards average	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

Variable	Units	Description	Intervals
PV power	kWh, mW/h	Photovoltaic power	1h

Special Parameters:

Name	Description	Example	Default
Kwp	Kilowatt peak production	&kwp=1	Null
Slope	Inclination of solar panel	&slope=20	Null
Facing	Orientation of solar panel	&facing=180	Null
Power efficiency	Power efficiency of pv module	&power_efficiency=0.9	0.85
Tracker	For solar panels using a sun tracker*	&tracker=1	Null

* Sun tracker definition

Mode	Description
1	Daily-1-axis-tracker
2	2-axis-tracker
3	Yearly-1-axis-tracker
4	DNI-tracker
5	Daily-1-axis-slope-tracker

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.

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

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

Variable	Units	Description	Intervals	Ensemble
Temperature	°C, °F	2m above ground	1h	GFS, ECMWF
Skin / Surface temperature	°C, °F	Soil surface or skin	1h	GFS
Wind speed	m/s, km/h, kn, mph, bf	10m above ground	1h	GFS, ECMWF
Wind direction	°, 2 char, 3 char	10m above ground	1h	GFS, ECMWF
Wind gusts	m/s, km/h, kn, mph, bf	10m above ground	1h	GFS
Precipitation	mm, inch	Water amount	1h	GFS, ECMWF
Low clouds	%	Cover of the sky	1h	GFS
Mid clouds	%	Cover of the sky	1h	GFS
High clouds	%	Cover of the sky	1h	GFS
GHI (Solar radiation)	W/m$^2$	Global horizontal radiation (backwards)	1h	GFS

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

Variable	Units	Description	Intervals	Aggregations (day)
Temperature	°C, °F	2m above ground	1h, day	Min, max, mean
Temperature spread	°C, °F	2m above ground, 1 StD from the mean temperature	1h, day
Precipitation	mm, inch	Water amount	1h, day	Sum
Precipitation spread	mm, inch	Water amount, 1 StD from the mean precipitation	1h, day
Precipitation probability	%		day
Predictability	%		day
Predictability class	0 - 5	0 = very low, 5 = very high	day
Wind speed	m/s, km/h, kn, mph, bf	10m above ground	1h, day	Min, max, mean
Wind speed spread	m/s, km/h, kn, mph, bf	10m above ground, 1 StD from the mean wind speed	1h, day
Wind direction	°, 2 char, 3 char	10m above ground	1h, day	Dominant
Sea level pressure	hPa	Corrected for sea level	1h, day	Min, max, mean
Relative humidity	%	Air humidity	1h, day	Min, max, mean
Total cloud cover	%	Cover of the sky, Analogue to METAR 0 - 8	1h, day	Min, max, mean
Total cloud cover spread	%	Cover of the sky, 1 StD from the mean cloud cover	1h, day
Snow fraction	0, 1	information whether precipitation falls as rain or snow: 0 = rain, 1 = snow	1h, day	Hourly: 0 or 1, aggregations: range from 0 till 1 (mean of hourly values)
Pictocode	1 - 35, 1 - 17	1h: 1 - 35 day/night pictos, day: 1 - 17 iday pictos	1h, day
GHI backwards	W/m$^2$ Wh/m$^2$	Global Horizontal Radiation	1h, day	Sum
Extraterrestrial radiation backwards	W/m$^2$ Wh/m$^2$	Extraterrestrial solar radiation	1h, day	Sum
Isdaylight	0, 1	1 = day, 0 = night	1h

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

Variable	Units	Description	Intervals	Aggregations (day)
Temperature	°C, °F	2m above ground	1h, day	Min, max, mean
Temperature spread	°C, °F	2m above ground, 1 StD from the mean temperature	1h, day
Felttemperature	°C, °F		1h, day	Min, max, mean
Precipitation	mm, inch	Water amount	1h, day	Sum
Precipitation spread	mm, inch	1 StD from the mean precipitation	1h, day
Precipitation probability	%		1h, day
Wind speed	m/s, km/h, kn, mph, bf	10m above ground	1h, day	Min, max, mean
Wind speed spread	m/s, km/h, kn, mph, bf	10m above ground, 1 StD from the mean wind speed	1h, day
Gust wind	m/skm/h, kn, mph, bf	10m above ground, 1 StD from the mean wind gust	1h, day
Wind direction	°, 2 char, 3 char	10m above ground	1h, day	Dominant
Sea level pressure	hPa	Corrected for sea level	1h, day	Min, max, mean
Relative humidity	%	Air humidity	1h, day	Min, max, mean
Total evapotranspiration*	mm, inch		1h, day	Sum
Reference evapotranspiration* (ET_0)	mm, inch		1h, day	Sum
Total cloud cover	%	Cloud cover, Cover of the sky	1h, day	Min, max, mean
Total cloud cover spread	%	Cover of the sky, 1 StD from the mean cloud cover	1h, day
Snow fraction	0, 1	information whether precipitation falls as rain or snow: 0 = rain, 1 = snow	1h, day	Hourly: 0 or 1, aggregations: range from 0 till 1 (mean of hourly values)
Pictocode	1 - 35, 1 - 17	1h: 1 - 35 day/night pictos, day: 1 - 17 iday pictos	1h, day
Low clouds	%	Cloud cover, Cover of the sky	1h, day	Min, max, mean
Mid clouds	%	Cloud cover, Cover of the sky	1h, day	Min, max, mean
High clouds	%	Cloud cover, Cover of the sky	1h, day	Min, max, mean
Sunshine time	min/h	Direct sunlight, Depends also on day length	1h, day	min/Interval
Visibility	km	Distance	1h, day	Min, max, mean
Skin/ Surface temperature	°C, °F	Soil surface or skin	1h, day	Min, max, mean
Dewpoint temperature	°C, °F	2m above ground	1h, day	Min, max, mean
CAPE			1h, day
Lifted index			1h, day
Predictability	%		day
Predictability class	0 - 5	0 = very low, 5 = very high	day
GHI backwards	W/m$^2$ Wh/m$^2$	Global horizontal radiation	1h, day	Sum
Extraterrestrial radiation backwards	W/m$^2$ Wh/m$^2$	Extraterrestrial solar radiation	1h, day	Sum
Isdaylight	0, 1	1 = day, 0 = night	1h
UV Index	0 - 11+	Ground level	day
Lifted index	J/kg	Risk of thunderstorms: Measure of atmospheric instability	1h, day	min

* 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

Variable	Units
coolingdegreedays_meananomaly	CDD
coolingdegreedays_meananomaly_trend	CDD
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_meananomaly	m
geopotentialheight_500mb_meananomaly_trend	m
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_meananomaly	HDD
heatingdegreedays_meananomaly_trend	HDD
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_meananomaly	hPa
sealevelpressure_probability_above_average	%
sealevelpressure_probability_below_average	%
sealevelpressure_probability_near_normal	%
shortwaveradiation_meananomaly	W/m2
shortwaveradiation_probability_above_average	%
shortwaveradiation_probability_below_average	%
shortwaveradiation_probability_near_normal	%
temperature_meananomaly	C°
temperature_meananomaly_trend	C°
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_meananomaly	m/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:

Content	Description
Probability below average	The probability that the selected variable will be in the lower 33.3% of the observed distribution from 1991 to 2020.
Probability near normal	The probability that the selected variable will be in the middle 33.3% of the observed distribution from 1991 to 2020.
Probability above average	The probability that the selected variable will be in the upper 33.3% of the observed distribution from 1991 to 2020.
Mean anomaly	Deviation from the weekly mean
Trend	The '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.

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.

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

Variable	Units
Temperature	°C, °F
Precipitation	mm
Sea surface temperature	°C, °F
Sea level pressure	hPa
Snow depth	m
Evapotranspiration	mm
Dewpoint temperature	°C, °F
Wind speed	m/s, km/h, kn, mph, bf
Total cloud cover	%