{"openapi":"3.1.2","info":{"title":"meteoblue Forecast API","description":"The Forecast API provides access to weather forecast data through a structured set of predefined data packages. Each package groups weather variables that are commonly used together for a specific purpose.\n\nThis structure is designed to make the API easier to use by providing use-case-specific datasets rather than requiring individual variable selection.\n\n# Overview\n\nThe Forecast API delivers point-based (retrieved for a specific geographic coordinate or station location) weather forecast data for locations worldwide. Forecast data are provided in predefined packages, each of which is available in different variants that control the time resolution.\n\nThe time resolution of a package is defined by adding a suffix to the package name (for example `-1h`, `-3h`, or `-day`). These suffixes provide access to the different variants of the same package.\n\nBecause of the design of the API, it is possible to query multiple packages with differing time resolutions within a single API request.\n\nFor most packages, several time resolutions are supported, ranging from fine-grained hourly data to coarser daily aggregations.\n\nLearn more about the features and use cases of the [Forecast API](https://business.meteoblue.com/products/weather-apis/premium-weather-api) on our website.\n\nConfigure and send API requests using the [Forecast API Configurator](https://www.meteoblue.com/en/weather-api/forecast-api/).\n\n## Key Packages\nThe following table lists the most commonly used packages and provides a short overview of their contents. More detailed information about each package is available in the corresponding package sections below.\n\n| Package | Contents |\n| ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Basic | Core weather variables such as temperature, precipitation, wind speed and direction, humidity, sea level pressure, UV index, and predictability. |\n| Current | Current weather conditions including temperature, wind speed and direction, and weather condition indicators derived from observations and model data. |\n| Sun & moon | Information on rise and set times of the Sun and Moon, as well as related illumination parameters. |\n| Agro | Data relevant for agricultural operations, including soil temperature, soil moisture, evapotranspiration, and vegetation-related variables. |\n| Wind | Wind speed and direction forecasts, including wind gusts and wind speeds at hub-height-relevant levels (e.g. 80 m). |\n| Clouds | Cloud cover information across different atmospheric layers and total cloudiness. |\n| Sea | Marine-related forecast variables such as wave height, wave period, sea surface temperature, and marine wind conditions. |\n| Solar | Solar radiation variables relevant for solar energy applications, including shortwave radiation components. |\n| PVPro | Solar power production forecasts based on power plant capacity, panel inclination, and panel orientation. |\n| Air | Atmospheric stability and convection-related variables such as CAPE and lifted index. |\n| Air quality | Forecasts of air quality variables, including pollutant concentrations. |\n| Trend | Ensemble-based 14-day forecasts for common weather variables, including information on forecast uncertainty. |\n| Multimodel | Weather variables from multiple numerical weather prediction models without post-processing, enabling analysis of forecast variability. |\n| Seasonal | Mean anomaly data for commonly used variables for the next 6 months and corresponding mean climate reference values |\n| Nowcast | Hyperlocal 6-hour forecast at 5-minute temporal resolution generated using radar data, lightning detection networks, satellite imagery, weather stations and the mLM |\n\n## Limitations\nAs mentioned packages can be combined, which is done by listing them and separated by the character `,`.\nFor various reasons, not all packages can be combined. In such cases, the API returns an error response describing the limitation.\nThe following list provides a general overview of packages that cannot be combined:\n- All requested minutely packages must have the same time resolution. For example, mixing `5min` and `10min` resolutions is not possible.\n- When using the CSV output format, only a single time resolution can be selected.\n- Seasonal anomaly packages cannot be combined with any other packages.\n- The packages `multimodel` and `multimodelsea` cannot be combined.\n- Multimodel variable packages (e.g. `multimodeltemperature-1h`) cannot be combined with each other or with most hourly or minutely packages.\n\n## Credits and Call Limits\n### API Keys and access\nAccess to the Forecast API is controlled via an API key. API keys are associated with a user account and are used to authenticate API requests.\n\nA user account may own multiple API keys, for example to separate usage across applications or environments. All API usage performed with an API key is attributed to the owning account.\n\nThe API key itself has to be provided as a URL query parameter (`apikey=YOUR_API_KEY`).\n\nAPI keys should be stored securely and must not be exposed publicly.\n\n### Usage accounting and limits\n\nAPI usage is accounted for based on credits, not on fixed call limits per package.\n\nEach API request consumes credits based on the requested data packages. When multiple time resolutions of the same package are requested in a single API call, only the most expensive resolution of that package is charged. Different packages are charged separately.\n\nFor example, requesting `basic-1h` and `basic-day` in the same call is charged as one basic package at the higher applicable cost of 8000 credits, not 12000. Similarly, requesting `basic-15min` and `basic-1h` is charged 8000 credits, not 16000. This rule applies to all packages.\n\nFor more information checkout the full list:\n\n
Full list of per package accounted credits\n\n| Package | Credits |\n| - | - |\n| agro-1h, -3h | 8000 |\n| agro-6h, -day | 4000 |\n| agromodelleafwetness-1h | 4000 |\n| agromodelsowing-1h | 4000 |\n| agromodelspray-1h | 4000 |\n| air-5min, -10min, -15min, -20min, -30min, -1h, -3h | 8000 |\n| air-6h, -day | 4000 |\n| airquality-1h, -3h | 8000 |\n| airquality-day | 4000 |\n| basic-5min, -10min, -15min, -20min, -30min, -1h, -3h | 8000 |\n| basic-6h, -day | 4000 |\n| clouds-5min, -10min, -15min, -20min, -30min, -1h, -3h | 8000 |\n| clouds-6h, -day | 4000 |\n| current | 4000 |\n| ensemble-1h | 16000 |\n| risk-1h | 8000 |\n| risk-day | 4000 |\n| precipitationrisk-1h | 8000 |\n| precipitationrisk-day | 4000 |\n| windrisk-1h | 8000 |\n| windrisk-day | 4000 |\n| activityindex-1h | 8000 |\n| activityindex-6h | 6000 |\n| activityindex-day | 4000 |\n| multimodel-1h, -3h, -6h | 16000 |\n| multimodelsea-1h, -3h, -6h, -day | 16000 |\n| multimodelwindpower-5min, -10min, -15min, -20min, -30min, -1h, -day | 16000 |\n| multimodelpv-5min, -10min, -15min, -20min, -30min, -1h, -day | 16000 |\n| multimodelwind-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelwind80-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelwinddirection-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelwinddirection80-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelclouds-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelprecipitation-5min, -10min, -15min, -20min, -30min, -1h, -day | 8000 |\n| multimodelradiation-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodelrh-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| multimodeltemperature-5min, -10min, -15min, -20min, -30min, -1h | 8000 |\n| sea-1h, -3h | 8000 |\n| sea-6h, -day | 4000 |\n| solar-5min, -10min, -15min, -20min, -30min, -1h | 16000 |\n| solar-3h, -6h, -day | 8000 |\n| solarensemble-5min, -10min, -15min, -20min, -30min, -1h | 16000 |\n| pvensemble-5min, -10min, -15min, -20min, -30min, -1h, -day | 16000 |\n| windpowerensemble-5min, -10min, -15min, -20min, -30min, -1h, -day | 16000 |\n| wind80ensemble-5min, -10min, -15min, -20min, -30min, -1h | 16000 |\n| sunmoon | 4000 |\n| sunmoontrend | 4000 |\n| trend-1h, -3h | 16000 |\n| trend-day | 8000 |\n| trendpro-1h, -3h | 32000 |\n| trendpro-day | 16000 |\n| wind-5min, -10min, -15min, -20min, -30min, -1h, -3h | 16000 |\n| wind-6h, -day | 8000 |\n| profiletemp-1h, -3h | 16000 |\n| profileheight-1h, -3h | 16000 |\n| profilerh-1h, -3h | 16000 |\n| profilewind-1h, -3h | 16000 |\n| profileclouds-1h, -3h | 16000 |\n| multimodelcloudprofile-1h, -3h | 16000 |\n| pvpro-5min, -10min, -15min, -20min, -30min, -1h | 16000 |\n| pvpro-day | 8000 |\n| seasonalanomaly-monthly | 32000 |\n| subseasonalanomaly-weekly | 3200000 |\n| sigmalevel-1h | 8000 |\n| sigmalevel-3h, -day | 4000 |\n| windpower-5min, -10min, -15min, -20min, -30min, -1h, -day | 16000 |\n| seeing-1h | 8000 |\n| snowice-5min, -10min, -15min, -20min, -30min, -1h, -3h | 8000 |\n| snowice-day | 4000 |\n| moonlight-5min, -10min, -15min, -20min, -30min, -1h | 4000 |\n| nowcast-5min, -10min, -15min | 8000 |\n| soiltrafficability-1h | 4000 |\n| icon-5min, -10min, -15min, -20min, -30min, -1h | 96000 |\n| iconeu-5min, -10min, -15min, -20min, -30min, -1h | 96000 |\n| icond2-5min, -10min, -15min, -20min, -30min, -1h | 96000 |\n| ifs025-5min, -10min, -15min, -20min, -30min, -1h | 96000 |\n| ifshres-5min, -10min, -15min, -20min, -30min, -1h | 96000 |\n\n
\n\nUsage statistics are available to provide transparency on consumed credits and API usage over time.\n\nDaily credit limits may be applied at two levels:\n\n- Account-level limits, which can be set to ensure overall API stability\n\n- API key-level limits, which can be configured by the user to prevent accidental overuse\n\nIf the configured daily credit limit is exceeded, subsequent API requests will result in an error response.\n\n**Without further agreement, we impose a rate limit of 500 calls per minute.** If you plan to download more than 10'000 data packages, please evenly distribute your calls over a few hours.","version":"2.0.0","x-logo":{"url":"https://static.meteoblue.com/assets/images/logo/meteoblue_logo_v2.0.png","backgroundColor":"hsl(210deg, 40%, 98%)","altText":"meteoblue","href":"https://docs.meteoblue.com/en/weather-apis/introduction/overview"}},"tags":[{"name":"Overview Structure"},{"name":"Core Packages","description":"Core packages provide access to the most used weather forecast data required for general-purpose applications across a wide range of domains. They include essential meteorological variables, current conditions, short- and medium-range forecasts, and domain-specific datasets such as wind, solar radiation, marine conditions, atmospheric stability, and air quality. Core packages are designed to support typical forecast use cases and can be queried individually or combined within a single request, depending on the required data and time resolution."},{"name":"Agronomical Packages","description":"Agronomical packages provide forecast variables that support agronomy-related assessments and decision making. These packages include soil and surface conditions as well as important hydrometeorological parameters beyond basic weather variables.\n\nThe Agronomical packages offer forecasts of variables such as evapotranspiration, soil moisture and soil temperature in the upper soil layer, dewpoint temperature, and leaf wetness indices, which can be used to understand water balance, soil conditions, and plant surface wetness. They also include various components of the surface energy balance such as sensible heat flux and reference evapotranspiration indicators.\n\nFor daily forecasts, Agronomical packages provide aggregated values such as maximum, mean, and minimum dewpoint temperature, soil moisture and soil temperature means and extremes, and wetbulb temperature statistics alongside mean leaf wetness metrics over the forecast period.\n\nIn addition to general Agronomical forecasts, specialised agricultural model packages target specific interests such as leaf wetness, sowing windows for various crops, and spray application windows. These models provide indices and time-series values relevant to surface conditions that influence agricultural operations.\n\nTogether, these agronomical forecasts support use cases where water balance, surface thermal conditions, soil moisture, and plant surface wetness information are required alongside standard weather variables."},{"name":"Renewable Energy Packages","description":"Renewable Energy packages provide forecast variables relevant for the assessment and planning of wind and solar energy production. These packages include wind speed and direction at hub-relevant heights, wind gust information, and solar radiation components that are used to characterise the available renewable energy resource at a given location.\n\nThe Renewable Energy packages support energy-related applications by delivering forecasts of key physical drivers such as wind conditions and solar irradiance, including variables relevant to solar power generation such as shortwave radiation and derived production estimates for photovoltaic systems. Wind energy forecasts include wind speeds at selected heights above ground that are relevant for turbine operation.\n\nThese packages are designed to complement general weather forecasts with variables that focus specifically on conditions affecting renewable energy systems."},{"name":"Advanced Packages","description":"The Advanced Packages provide specialised forecast data that extends beyond general weather conditions to include additional atmospheric and environmental variables. This includes data on sea state (such as wave height and wave direction), atmospheric stability and dynamics (such as CAPE, lifted index, and helicity), and air quality indicators (such as concentrations of ozone and particulate matter). These packages are intended for use cases that require advanced environmental metrics alongside standard meteorological variables."},{"name":"Ensemble and Probabilistic Forecasting Packages","description":"Ensemble and probabilistic packages provide forecast outputs derived from multiple model members rather than a single deterministic forecast. In addition to individual members, these packages may include aggregated statistics (such as consensus forecasts, minimum and maximum values, and percentile-based values) to help describe the range of possible outcomes and forecast uncertainty for a given location and time."},{"name":"Multimodel Packages","description":"Multimodel packages provide forecasts derived from the combination of outputs from multiple independent numerical weather prediction models. Rather than representing a range of outcomes from a single model (as in ensemble forecasts), multimodel forecasts integrate information from different forecast systems to improve robustness and reduce model-specific biases."},{"name":"14-Day Forecast Packages","description":"The 14-Day Forecast Packages provide extended weather forecast data covering up to 14 days ahead. These packages are designed for applications that require insight into longer-range weather patterns beyond the standard short- and medium-range forecasts. They include forecast variables similar to other package groups (such as temperature, precipitation, wind, cloud cover, and derived indicators) and are structured to support analysis over an extended forecast horizon.\n\nThese packages should be used when long-term weather outlooks are required, for example in planning and decision-making processes that extend beyond the typical 5- to 7-day forecast period. The data in these packages allow users to assess expected conditions and trends over the 14-day window, while recognising that forecast certainty generally declines with increasing lead time."},{"name":"Long Term Forecasts","description":"The Long-Term Forecasts group provides extended horizon forecast data that goes beyond the typical short- and medium-range periods. These packages are designed for applications where insight into weather tendencies over more distant future dates is required, such as climate trend analysis, planning, or seasonal outlooks.\n\nLong-term forecasts include variables related to temperature, precipitation, and other commonly used meteorological parameters, delivered over a forecast window that extends into the more distant future. Because uncertainty increases with lead time, these forecasts emphasise broad tendencies rather than precise daily conditions.\n\nLong-Term Forecasts should be used when you need insight into general patterns and expected conditions beyond the range of standard 7- to 14-day forecasts."},{"name":"Custom Risk Packages","description":"The Custom Risks package contains experimental forecast endpoints that offer risk and hazard indicators derived from one or more meteorological variables. These endpoints provide specialised indices designed to assess the likelihood or severity of specific weather-related risks, such as fire risk or other environmental stressors. Because these products are experimental, they may evolve over time in terms of available variables, calculation methods, and output formats.\n\nCustom Risks packages should be used when the application requires risk-focused forecast information in addition to standard meteorological data. Note that experimental endpoints may be updated or extended more frequently than stable package groups."},{"name":"Raw Forecast","description":"The Raw Forecast package provides direct access to forecast outputs from individual numerical weather prediction models. Unlike processed or blended packages, raw forecast data reflects the selected models output with minimal transformation.\nThis package is intended for users who require model-specific data for analysis, comparison, research, or custom post-processing. By selecting a specific forecast model, users can access its native output and apply their own validation, correction, or aggregation methods as needed.\nRaw Forecast package differs from deterministic, multimodel, or ensemble products in that they do not combine, statistically adjust, or optimise model results beyond necessary interpolation to the requested resolution."}],"servers":[{"url":"https://my.meteoblue.com"}],"security":[{"apikey":[]}],"paths":{"/packages/{packages}":{"parameters":[{"name":"packages","in":"path","required":true,"schema":{"type":"array","examples":["basic-1h","basic-1h,basic-day"],"items":{"type":"string","enum":["agro-1h","agro-3h","agro-6h","agro-day","agromodelleafwetness-1h","agromodelsowing-1h","agromodelspray-1h","air-5min","air-10min","air-15min","air-20min","air-30min","air-1h","air-3h","air-6h","air-day","airquality-1h","airquality-3h","airquality-day","basic-5min","basic-10min","basic-15min","basic-20min","basic-30min","basic-1h","basic-3h","basic-6h","basic-day","clouds-5min","clouds-10min","clouds-15min","clouds-20min","clouds-30min","clouds-1h","clouds-3h","clouds-6h","clouds-day","current","ensemble-1h","risk-1h","risk-day","precipitationrisk-1h","precipitationrisk-day","windrisk-1h","windrisk-day","activityindex-1h","activityindex-6h","activityindex-day","multimodel-1h","multimodel-3h","multimodel-6h","multimodelsea-1h","multimodelsea-3h","multimodelsea-6h","multimodelsea-day","multimodelwindpower-5min","multimodelwindpower-10min","multimodelwindpower-15min","multimodelwindpower-20min","multimodelwindpower-30min","multimodelwindpower-1h","multimodelwindpower-day","multimodelpv-5min","multimodelpv-10min","multimodelpv-15min","multimodelpv-20min","multimodelpv-30min","multimodelpv-1h","multimodelpv-day","multimodelwind-5min","multimodelwind-10min","multimodelwind-15min","multimodelwind-20min","multimodelwind-30min","multimodelwind-1h","multimodelwind80-5min","multimodelwind80-10min","multimodelwind80-15min","multimodelwind80-20min","multimodelwind80-30min","multimodelwind80-1h","multimodelwinddirection-5min","multimodelwinddirection-10min","multimodelwinddirection-15min","multimodelwinddirection-20min","multimodelwinddirection-30min","multimodelwinddirection-1h","multimodelwinddirection80-5min","multimodelwinddirection80-10min","multimodelwinddirection80-15min","multimodelwinddirection80-20min","multimodelwinddirection80-30min","multimodelwinddirection80-1h","multimodelclouds-5min","multimodelclouds-10min","multimodelclouds-15min","multimodelclouds-20min","multimodelclouds-30min","multimodelclouds-1h","multimodelprecipitation-5min","multimodelprecipitation-10min","multimodelprecipitation-15min","multimodelprecipitation-20min","multimodelprecipitation-30min","multimodelprecipitation-1h","multimodelprecipitation-day","multimodelradiation-5min","multimodelradiation-10min","multimodelradiation-15min","multimodelradiation-20min","multimodelradiation-30min","multimodelradiation-1h","multimodelrh-5min","multimodelrh-10min","multimodelrh-15min","multimodelrh-20min","multimodelrh-30min","multimodelrh-1h","multimodeltemperature-5min","multimodeltemperature-10min","multimodeltemperature-15min","multimodeltemperature-20min","multimodeltemperature-30min","multimodeltemperature-1h","sea-1h","sea-3h","sea-6h","sea-day","solar-5min","solar-10min","solar-15min","solar-20min","solar-30min","solar-1h","solar-3h","solar-6h","solar-day","solarensemble-1h","solarensemble-5min","solarensemble-10min","solarensemble-15min","solarensemble-20min","solarensemble-30min","pvensemble-day","pvensemble-1h","pvensemble-5min","pvensemble-10min","pvensemble-15min","pvensemble-20min","pvensemble-30min","windpowerensemble-day","windpowerensemble-1h","windpowerensemble-5min","windpowerensemble-10min","windpowerensemble-15min","windpowerensemble-20min","windpowerensemble-30min","wind80ensemble-1h","wind80ensemble-5min","wind80ensemble-10min","wind80ensemble-15min","wind80ensemble-20min","wind80ensemble-30min","sunmoon","sunmoontrend","trend-1h","trend-3h","trend-day","trendpro-1h","trendpro-3h","trendpro-day","wind-5min","wind-10min","wind-15min","wind-20min","wind-30min","wind-1h","wind-3h","wind-6h","wind-day","profiletemp-1h","profileheight-1h","profilerh-1h","profilewind-1h","profileclouds-1h","profiletemp-3h","profileheight-3h","profilerh-3h","profilewind-3h","profileclouds-3h","multimodelcloudprofile-1h","multimodelcloudprofile-3h","pvpro-5min","pvpro-10min","pvpro-15min","pvpro-20min","pvpro-30min","pvpro-1h","pvpro-day","seasonalanomaly-monthly","subseasonalanomaly-weekly","sigmalevel-1h","sigmalevel-3h","sigmalevel-day","windpower-5min","windpower-10min","windpower-15min","windpower-20min","windpower-30min","windpower-1h","windpower-day","seeing-1h","snowice-5min","snowice-10min","snowice-15min","snowice-20min","snowice-30min","snowice-1h","snowice-3h","snowice-day","moonlight-5min","moonlight-10min","moonlight-15min","moonlight-20min","moonlight-30min","moonlight-1h","nowcast-5min","nowcast-10min","nowcast-15min","soiltrafficability-1h","icon-1h","iconeu-1h","icond2-1h","ifs025-1h","ifshres-1h","icon-5min","iconeu-5min","icond2-5min","ifs025-5min","ifshres-5min","icon-10min","iconeu-10min","icond2-10min","ifs025-10min","ifshres-10min","icon-15min","iconeu-15min","icond2-15min","ifs025-15min","ifshres-15min","icon-20min","iconeu-20min","icond2-20min","ifs025-20min","ifshres-20min","icon-30min","iconeu-30min","icond2-30min","ifs025-30min","ifshres-30min"],"description":"An available Package of the Forecast API"},"minItems":1,"uniqueItems":true},"description":"One or more distinct packages from the Forecast API as a list separated by the character `,`.\n\nEach package contributes its own data to the response. Detailed descriptions of the available packages are provided in the `Package Catalogue` section."},{"name":"forecastDays","in":"query","schema":{"type":"integer","minimum":0},"description":"To limit the number of days which is returned set this query-parameter to the number of days which your application requires.\nIf this parameter is not set the API returns as many forecast-days as it can, which might be more than 7 days.\nWhen the selected number of forecast-days is greater than the number of available days only the maximum number of days is returned.\n\nThe resulting time-range of `historyDays` and `forecastDays` must contain at least one day."},{"name":"historyDays","in":"query","schema":{"type":"integer","default":0,"maximum":4,"minimum":0},"description":"Specifies how many past days should be returned. By default, no historical data are returned.\n\nData from the past is processed slightly differently than the data for the future, depending on how many days have passed:\n- For the processing satellite-data and model-data are used regardless of the days in the past\n- Measurement data is only considered up to 3 days into the past\n- Radar data is only considered up to 1 day into the past\n\nThe resulting time-range of `historyDays` and `forecastDays` must contain at least one day."},{"name":"lat","in":"query","schema":{"type":"number","description":"A Latitude value in degrees (WGS 84) between `-90.0` and `90.0`.","examples":[47.5596],"maximum":90.0,"minimum":-90.0},"description":"Latitude of the location, in degrees (WGS 84). This parameter must be specified if no station ID is provided."},{"name":"lon","in":"query","schema":{"type":"number","description":"A Longitude value in degrees (WGS 84) between `-180.0` and `180.0`.","examples":[7.5886],"maximum":180.0,"minimum":-180.0},"description":"Longitude of the location, in degrees (WGS 84). This parameter must be specified if no station ID is provided."},{"name":"asl","in":"query","schema":{"type":"number","description":"Height above sea level measured in meters.","examples":[0.0],"maximum":9000.0,"minimum":-500.0},"description":"The elevation above sea level in metres for the location of interest. If not specified an elevation is inferred from the given location using an 80 metre resolution digital elevation model (`DEM`).\nSpecifying an elevation can improve forecast accuracy, as the API applies elevation corrections to the returned variables.\nEspecially in complex alpine terrain, the Forecast API behaves different for coordinates in a valley and on the mountain."},{"name":"station","in":"query","schema":{"type":"string","description":"A Station Identifier.","examples":["MLM*API*METEOSCHWEIZ_BAS","MOS*API*METEOSCHWEIZ_BAS"],"minLength":1},"description":"You can provide a station identifier instead of `lat` and `lon`. For some variables, the mLM forecast is optimised using data from the specified station. The requested station must be active and have a sufficient history of high-quality data. Requests for stations that do not fulfil these requirements may fail or produce faulty results.\n\nThe variables being optimised are common weather-station variables like temperature, relative humidity, wind and precipitation and all variables than can be derived from these.\n\n_Access to this parameter is restricted. For more details you can [contact us](mailto:support@meteoblue.com) directly._"},{"name":"name","in":"query","schema":{"type":"string","examples":["name_to_be_returned_in_response"]},"description":"Custom name which can optionally be supplied to be returned in the response. This parameter is returned as is and is not used for any other purpose.\nSpecial characters must be URL-encoded."},{"name":"slope","in":"query","schema":{"type":"number","examples":[30.0],"maximum":90.0,"minimum":0.0},"description":"This parameter applies to the solar power-related packages.\n\nSpecifies the inclination angle of the solar panel in degrees, measured from the horizontal plane (0° = horizontal, 90° = vertical).\""},{"name":"facing","in":"query","schema":{"type":"number","examples":[180.0],"maximum":360.0,"minimum":-360.0},"description":"This parameter applies to the solar power-related packages.\n\nSpecifies the azimuth orientation of the solar panel in degrees, measured clockwise from north (0° = north, 90° = east, 180° = south, 270° = west)."},{"name":"tracker","in":"query","schema":{"type":"integer","enum":[0,1,2,3,4,5],"default":0,"examples":[0]},"description":"This parameter applies to the solar power-related packages.\n\nIndicates the type of sun-tracking system used by the solar panel, if applicable.\n\nDepending on what tracker is used the `slope` or `facing` parameters need to be set.\nThe following table gives some more information:\n\n| ID | Tracker type | Slope (tilt) | Facing (azimuth) |\n|-|-|-|-|\n| 0 | No Tracker | Fixed | Fixed |\n| 1 | Daily vertical axis tracker | Fixed | Moves daily |\n| 2 | Daily 2-axis tracker | Moves daily | Moves daily |\n| 3 | Yearly horizontal tracker | Changes yearly | Fixed (usually South) |\n| 4 | Daily DNI tracker | Moves daily | Moves daily |\n| 5 | Daily horizontal axis tracker | Moves daily | Fixed |"},{"name":"turbineid","in":"query","schema":{"type":"integer","description":"Turbine id identifies a specific type of wind-turbine. Use -1 for a standard wind-turbine","externalDocs":{"description":"Provides a list of supported wind turbine IDs.","url":"https://meteoblue.sharepoint.com/:x:/s/External/EUP28ffPboNKtTSiCQNF1aIBhIE14sA9j7mGareWi8YUOg?e=x76BCe"},"examples":[-1,1],"minimum":-1},"description":"This parameter applies to the wind power-related package.\n\nSpecifies the wind turbine type using a numeric ID."},{"name":"numberofturbines","in":"query","schema":{"type":"integer","default":1,"minimum":1},"description":"This parameter applies to the wind power-related package.\n\nSpecifies the number of turbines at the specified location."},{"name":"kwp","in":"query","schema":{"type":"number","examples":[1000],"exclusiveMinimum":0.0},"description":"This parameter applies to packages related to solar and wind power.\n\nPeak kilowatt capacity/production of a solar-panel and/or wind-turbine.\nFor wind turbines, this parameter is only applicable to the standard turbine (`turbineid=-1`)."},{"name":"power_efficiency","in":"query","schema":{"type":"number","description":"A fractional value which is between `0.0` and `1.0`.","examples":[0.0,0.5,1.0],"maximum":1.0,"minimum":0.0},"description":"This parameter applies to packages related to solar and wind power.\n\nThe power efficiency as a fraction.\nIf no value is supplied, a default value of `0.85` is used for solar power and `1.0` for wind power."},{"name":"sigmalevel","in":"query","schema":{"type":"number","maximum":18000.0,"minimum":10.0},"description":"Used by a number of packages to apply a height-based correction on the data. Various packages support different heights.\n\nSpecifies the elevation above ground level, in metres."},{"name":"domain","in":"query","schema":{"type":"string","enum":["NEMS4","NEMS12","NEMSGLOBAL","NEMSIN","NEMSAS02","NEMSAF01","NEMSSA","ICON","ICONEU","ICOND2","GFS05","NAM12","NAM5","NAM3","HRRR","MFGLOBAL","MFEU","MFFR","GEM15","GEM2","MSM","UKMO2","NBM","WRFAMS"],"minLength":1},"description":"Specifies the domain from which the data are retrieved. By default the API uses data from different models and combines them into a single value optimised for the selected location. Specifying a domain overrides the default model selection behaviour.\n\nIn most cases, this parameter should not be set."},{"name":"raw","in":"query","schema":{"type":"boolean","default":false},"description":"If a raw model forecast is required, this query parameter can be used to request it. By default, data from multiple models are combined, and post-processing techniques are applied to improve data quality.\n\nIn most cases, this parameter should not be set."},{"name":"tz","in":"query","schema":{"type":"string","externalDocs":{"description":"List of timezones which are included in the Timezone Database.","url":"https://en.wikipedia.org/wiki/List_of_tz_database_time_zones"},"examples":["utc","Europe%2Fzurich"]},"description":"Timezone identifier as specified in the timezone database.\n\nIf no time zone is specified, the API will detect the time zone automatically. For coordinates at sea, the API attempts to determine a nearby coastal time zone (up to approximately 50 km), otherwise `utc` is used.\n\nFor automated systems and further data processing, the use of UTC without local time zone offsets or seasonal time changes is recommended.\n\nFor timezones with daylight saving time, only the time-offset at the time of the API call will be used. There will be no daylight saving time switches in the actual data. So if a place switches from Summertime to Wintertime on Sunday (20.11.2019) and the api is called on Saturday (19.11.2019), all days of the forecasts will use Summertime.\n\nFor time zones with fractional hour offsets (for example, Asia/Kolkata at UTC+05:30), the offset is rounded to a full hour internally."},{"name":"timeformat","in":"query","schema":{"type":"string","enum":["iso8601","timestamp_utc","timestamp_ms_utc","YMD","Y-M-D"],"default":"Y-M-D","examples":["Y-M-D"]},"description":"Specifies the format in which time values are returned."},{"name":"format","in":"query","schema":{"type":"string","enum":["json","csv","xlsx","highcharts","highchartsHtml"],"default":"json","examples":["json"]},"description":"Specifies the format in which the response is returned.\n\n*Note that the CSV format does not support mixing different time resolutions and is not compatible with all packages. Make sure to always parse the header and check the column location of the queried variable, as these positions might change, when new variables are added and this might happen without any communication from meteoblue.*"},{"name":"temperatureUnit","in":"query","schema":{"type":"string","enum":["C","K","F"],"default":"C","examples":["C"],"x-enumDescriptions":{"C":"Celsius","K":"Kelvin","F":"Fahrenheit"}},"description":"Specifies the unit used for temperature values in the response."},{"name":"windSpeedUnit","in":"query","schema":{"type":"string","enum":["m/s","km/h","mph","kn","bft"],"default":"m/s","x-enumDescriptions":{"m/s":"meter per second","km/h":"kilometer per hour","mph":"Miles per hour","kn":"Knots","bft":"Beaufort"}},"description":"Specifies the unit used for wind speed values in the response."},{"name":"windDirectionUnit","in":"query","schema":{"type":"string","enum":["degree","2char","3char"],"default":"degree","examples":["degree"]},"description":"Specifies the unit used for wind direction values in the response."},{"name":"precipitationUnit","in":"query","schema":{"type":"string","enum":["metric","imperial"],"default":"metric","examples":["metric"]},"description":"Specifies the unit used for precipitation values in the response."}],"get":{"tags":["Overview Structure"],"summary":"Forecast","description":"The Forecast API provides a range of packages that group weather variables by use case. 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It uses state-of-the-art forecast technologies, such as mLM and nowcasting, with real-time corrections based on nearby weather station, satellite, and radar observations.\n\nThe Basic package provides a 7-day forecast of key meteorological variables, including precipitation, temperature, wind speed and direction, humidity, sea level pressure, UV index, and predictability. Weather conditions are represented using numeric codes rather than descriptive pictograms.\n\nThe [7-day weather forecast on the meteoblue website](https://www.meteoblue.com/en/weather/week/basel_switzerland_2661604) uses the Basic package to display daily and 3-hourly data. The data provided via the website and the API are identical.\n\n### Temperature\n\nThe `temperature` field is based on the mLM temperature forecast and represents air temperature at 2 metres above ground.\n\nIn regions with complex terrain, such as the Alps and parts of Central Europe, meteoblue uses specialised high-resolution model domains (up to 700 m resolution) to better capture local temperature patterns. As a result, elevation changes can significantly alter the shape of the temperature curve; for example, on a mountain peak, the diurnal temperature variations observed in a nearby valley may be greatly reduced.\n\nOutside Central Europe, less complex elevation corrections are applied to account for differences between model topography and real topography. The elevation of the local topography at a given location is automatically determined using a digital elevation model with 80 m resolution, but it can also be specified manually using the `&asl=` query parameter.\n\nIf measurements from a nearby weather station are available, the temperature forecast is optimised using data from that station.\n\nA height of 2 metres above ground is most used for air temperature forecasts. Temperature forecasts for the surface and within the soil are provided as part of the Agro package.\n\nThe 2-metre air temperature may not represent the perceived temperature. High humidity and intense radiation tend to increase perceived temperature, while strong winds tend to decrease it. The `felttemperature` field combines these factors to provide an estimate of perceived conditions.\n\n### Precipitation\n\nThe `precipitation` field represents the total amount of precipitation, including rain, snow, ice, and hail. Convective precipitation refers specifically to precipitation associated with convective processes and only includes showers. Both fields **must not** be summed up.\n\nSnowfall can be estimated by combining the precipitation values with the corresponding snow fraction. The resulting snowfall amount, expressed in millimetres, can be multiplied by a factor of 7 to approximate snow depth; for example, 1 mm of precipitation corresponds approximately to 7 mm of snowfall.\n\nThe precipitation in the Basic package is calculated using multiple forecast models combined with the meteoblue mLM approach. Radar observations are used to apply corrections to recent past data and short-range forecasts through radar nowcasting. These corrections apply to both hourly data and daily aggregations.\n\nFor hourly and 3-hourly data, the precipitation value represents the total amount over the respective preceding time interval, comparable to the way precipitation is measured by a rain gauge. For example, the precipitation value reported at `12:00` for 3-hourly data represents the accumulated precipitation from `09:00` to `12:00`.\n\nTo visualise precipitation in the surrounding area, the Basic package provides precipitation information on a 7×7 grid around the queried location. Further details on this output are described in the response schema.\n\nNote that we strongly discourage users from trying to build their own logic for making precipitation based on precipitation probabilities. We spent years of development calibrating our systems, our determinsitic precipitation is based on complex processing of dozens of weather models, ensemble forecast systems, probabilties, radar and satellite data.\n\n### Precipitation Probability (POP)\n\nThe probability of precipitation is the probability of precipitation occuring in the preceeding 3h (regardless if the feed is 1h or 3h time resolution).\n\nFor daily data it is the probability of precipitation occuring within the 24h of the given day.\n\nNote that meteoblue provides other precipitation probabilities (for higher threshold values and also for other time aggregations, 1h, 6h, 12h suitable for special applications. Consult one of our experts for custom solutions if you have an already calibrated probabilistic response model for your business so that we can provide you the proper kind of probability.\n\n### Weather Condition Pictogram\n\nWeather conditions (for example: \"Clear, cloudless sky\", \"Partly cloudy\", or \"Overcast with rain\") are represented using numeric pictogram codes.\n\nHourly and daily pictograms use different code ranges. The Basic package provides hourly pictogram codes in the range 1 - 35 and daily pictogram codes in the range 1 - 25.\n\nA daylight indicator can be used to select the appropriate Daytime or Nighttime pictogram.\n\nFor 3-hourly data, pictogram codes use the same numeric codes as hourly pictograms. For 6-hourly data, pictogram codes use the same numeric codes as daily pictograms. For example, for 3-hourly data, the pictogram reported at `12:00` represents the conditions over the preceding 3-hour interval (`09:00` to `12:00`).\n\nWe strongly discourage users to derive their own pictograms based on weather data.\n\n\n### Wind Speed and Direction\n\nWind speed forecasts are based on the meteoblue mLM approach and represent wind speed at 10 metres above ground.\n\nWind speeds closer to the ground are typically lower. To approximate wind speed at 2 metres above ground, the 10 m wind speed can be multiplied by a factor of `0.74`, which provides a reasonable approximation on average.\n\nWind speed varies over time and across spatial grid cells. Hourly wind speed values represent an average over the respective one-hour interval and model grid cell. As a result, wind gusts, which represent short-duration peak wind speeds, may be substantially higher than the corresponding hourly mean wind speed. 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By combining the outputs of multiple forecast models using statistical methods and machine learning techniques, meteoblue produces a learning multi-model forecast (mLM). An outcome of this approach is the ability to estimate the expected accuracy of the forecast for a given location.\n\nPredictability indicates the level of agreement among the forecast model outputs for a specific location and time. When forecast results show a high level of agreement, predictability is correspondingly high. 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}\n}"}]}},"/packages/{pvensemble-package}":{"parameters":[{"name":"pvensemble-package","in":"path","required":true,"schema":{"type":"array","examples":["pvensemble-day","pvensemble-day,pvensemble-1h"],"items":{"type":"string","enum":["pvensemble-day","pvensemble-1h","pvensemble-5min","pvensemble-10min","pvensemble-15min","pvensemble-20min","pvensemble-30min"],"description":"An available Package of the Packages API"},"minItems":1,"uniqueItems":true},"description":"Combination of one or more distinct packages from the Packages API. 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milliseconds.","examples":[1735689600000]},"minItems":1},{"type":"array","items":{"type":"string","description":"Date-Time in format YYYYMMDD hh:mm","examples":["20250806 12:21"],"pattern":"\\d{6} \\d\\d:\\d\\d"},"minItems":1},{"type":"array","items":{"type":"string","description":"Date-Time in format YYYYMMDD hh:mm","examples":["20250806"],"pattern":"\\d{6}"},"minItems":1},{"type":"array","items":{"type":"string","description":"Date-Time in format YYYY-MM-DD hh:mm","examples":["2025-08-29 12:21"],"pattern":"\\d{4}-\\d\\d-\\d\\d \\d\\d:\\d\\d"},"minItems":1},{"type":"array","items":{"type":"string","description":"Date-Time in format YYYY-MM-DD hh:mm","examples":["2025-08-29"],"pattern":"\\d{4}-\\d\\d-\\d\\d"},"minItems":1}],"description":"Specifies the UTC initialisation time of the forecast model run(s)."},"modelrun_updatetime_utc":{"anyOf":[{"type":"string","format":"date-time","description":"Date-Time in format ISO8601","examples":["2025-08-06T12:21:00+00:00"]},{"type":"integer","description":"A utc-timestamp value in seconds.","examples":[1735689600]},{"type":"integer","description":"A utc-timestamp value in milliseconds.","examples":[1735689600000]},{"type":"string","description":"Date-Time in format YYYYMMDD hh:mm","examples":["20250806 12:21"],"pattern":"\\d{6} \\d\\d:\\d\\d"},{"type":"string","description":"Date-Time in format YYYYMMDD hh:mm","examples":["20250806"],"pattern":"\\d{6}"},{"type":"string","description":"Date-Time in format YYYY-MM-DD hh:mm","examples":["2025-08-29 12:21"],"pattern":"\\d{4}-\\d\\d-\\d\\d \\d\\d:\\d\\d"},{"type":"string","description":"Date-Time in format YYYY-MM-DD hh:mm","examples":["2025-08-29"],"pattern":"\\d{4}-\\d\\d-\\d\\d"}],"description":"Completion time of the last model run."},"models":{"type":"array","description":"Lists the models included in multimodel packages.","items":{"type":"string","examples":["ICON"]}},"domain":{"type":"string","description":"If a specific domain was provided this field is set to it's value.","examples":["ICON"]},"gfsensemble_members":{"type":"array","description":"Lists the GFS members in ensemble packages.","items":{"type":"string","examples":["member_001"]},"minItems":1},"ecmwfensemble_members":{"type":"array","description":"Lists the ECMWF members in ensemble packages.","items":{"type":"string","examples":["member_001"]},"minItems":1},"gridpointelevation":{"oneOf":[{"type":["number","null"],"examples":[0]},{"type":"array","items":{"type":"number","examples":[0]}}],"description":"The elevations of the model or models for the selected grid point."},"sigmalevel":{"type":"number","description":"If a specific sigmaLevel was queried this will be set to it's value.","examples":[30]},"kwp":{"type":["number","null"],"description":"If a kwp for solar-power related packages was provided this will be it's value."},"slope":{"type":"number","description":"If a solar-panel slope was provided this will be set to it's value.","examples":[20]},"facing":{"type":"number","description":"If a solar-panel facing orientation was provided this will be set to it's value.","examples":[180]},"tracking":{"type":"integer","description":"If a solar-panel sun-tracking was provided this will be set to it's value.","examples":[0]},"generation_time_ms":{"type":"number","description":"Time taken to generate the response.","examples":[13.342023],"minimum":0.0},"pressurelevels_clouds":{"type":"array","description":"Lists the pressure levels of the different clouds for the multimodelcloudprofile package.","items":{"type":"number","examples":[1000]}},"turbinetype":{"type":"string","description":"If a wind-turbine type was provided this will be set to it's value.","examples":["Default Generic Turbine"]},"forecasttype":{"type":"string","description":"The processing type of forecast. Note that the type `MOS` is only available for queries providing a station id.","examples":["RAW","MOS"]},"numberofturbines":{"type":"integer","description":"If a number of turbines was provided this will be set to it's value.","examples":[1],"minimum":1},"powerefficiency":{"type":"number","description":"If a power efficiency was provided this will be set to it's value.","examples":[1]},"turbinepeakpower":{"type":"number","description":"If a kwp for wind-power related packages was provided this will be it's value."},"stationid":{"type":"string","description":"If a specific station was provided this will be set to it's value.","examples":["MLM*API*METEOSCHWEIZ_BAS"],"minLength":1}},"required":["name","latitude","longitude","height","timezone_abbrevation","utc_timeoffset","modelrun_utc","modelrun_updatetime_utc","generation_time_ms"]},"unitsObject":{"type":"object","description":"Meta-Data about units used in the result.","properties":{"time":{"type":"string","examples":["YYYY-MM-DD hh:mm"]},"precipitation_probability":{"type":"string","examples":["percent"]},"pressure":{"type":"string","examples":["hPa"]},"surfaceairpressure":{"type":"string","examples":["hPa"]},"relativehumidity":{"type":"string","examples":["percent"]},"precipitation":{"type":"string","examples":["mm"]},"predictability":{"type":"string","examples":["percent"]},"geopotentialheight":{"type":"string","examples":["m"]},"temperature":{"type":"string","examples":["C"]},"windspeed":{"type":"string","examples":["ms-1"]},"winddirection":{"type":"string","examples":["degree"]},"sunshinetime":{"type":"string","examples":["minutes"]},"cloudcover":{"type":"string","examples":["percent"]},"visibility":{"type":"string","examples":["m"]},"density":{"type":"string","examples":["kg/m³"]},"ozone":{"type":"string","examples":["μg/m³"]},"dust_concentration":{"type":"string","examples":["μg/m³"]},"pm25":{"type":"string","examples":["μg/m³"]},"pm10":{"type":"string","examples":["μg/m³"]},"so2":{"type":"string","examples":["μg/m³"]},"no2":{"type":"string","examples":["μg/m³"]},"icing":{"type":"string","examples":["mm"]},"co":{"type":"string","examples":["μg/m³"]},"pollen_birch":{"type":"string","examples":["grains/m³"]},"pollen_grass":{"type":"string","examples":["grains/m³"]},"pollen_olive":{"type":"string","examples":["grains/m³"]},"aod550":{"type":"string","examples":[""]},"airqualityindex":{"type":"string","examples":["index"]},"wave_height":{"type":"string","examples":["m"]},"wave_period":{"type":"string","examples":["s"]},"wave_direction":{"type":"string","examples":["degree"]},"currentvelocity":{"type":"string","examples":["m/s"]},"salinity":{"type":"string","examples":["g/kg"]},"radiation":{"type":"string","examples":["Wm-2"]},"transpiration":{"type":"string","examples":["mm"]},"cape":{"type":"string","examples":["Jkg-1"]},"soilmoisture":{"type":"string","examples":["volumetric percent"]},"power":{"type":"string","examples":["kW"]},"pvpower":{"type":"string","examples":["kW"]},"windpower":{"type":"string","examples":["kW"]},"iam":{"type":"string","examples":["percent"]},"snowcover":{"type":"string","examples":["mm"]},"radiationtotal":{"type":"string","examples":["Whm-2"]},"powertotal":{"type":"string","examples":["kWh"]},"snowmelt":{"type":"string","examples":["mm"]},"snowdepth":{"type":"string","examples":["m"]},"snowaccumulation":{"type":"string","examples":["mm"]},"probability":{"type":"string","examples":["percent"]},"daylightintegral":{"type":"string","examples":["mol*m-2*day-1"]},"lightintensity":{"type":"string","examples":["umol*m-2"]},"helicity":{"type":"string","examples":["m2s-2"]},"convectiveinhibition":{"type":"string","examples":["Jkg-1"]},"boundarylayerheight":{"type":"string","examples":["m"]},"cloudwater":{"type":"string","examples":["g"]},"cloudice":{"type":"string","examples":["g"]},"freezinglevelheight":{"type":"string","examples":["m a.s.l."]},"leafwetness":{"type":"string","examples":["fraction"]},"sensibleheatflux":{"type":"string","examples":["Wm-2"]},"moonlight":{"type":"string","examples":["percent"]},"skybrightness":{"type":"string","examples":["lx"]}}}},"responses":{"error-response":{"description":"Error","content":{"application/json":{"schema":{"type":"object","properties":{"error":{"type":"boolean","const":true,"description":"Flag indicating that an error has occurred."},"error_message":{"type":"string","description":"Message describing the error."}},"required":["error","error_message"]},"examples":{"Error Message Example":{"summary":"Example Error","description":"Example of a possible error message","value":{"error":true,"error_message":"Message describing the error."}}}}}}},"parameters":{"forecastDays":{"name":"forecastDays","in":"query","schema":{"type":"integer","minimum":0},"description":"To limit the number of days which is returned set this query-parameter to the number of days which your application requires.\nIf this parameter is not set the API returns as many forecast-days as it can, which might be more than 7 days.\nWhen the selected number of forecast-days is greater than the number of available days only the maximum number of days is returned.\n\nThe resulting time-range of `historyDays` and `forecastDays` must contain at least one day."},"historyDays":{"name":"historyDays","in":"query","schema":{"type":"integer","default":0,"maximum":4,"minimum":0},"description":"Specifies how many past days should be returned. By default, no historical data are returned.\n\nData from the past is processed slightly differently than the data for the future, depending on how many days have passed:\n- For the processing satellite-data and model-data are used regardless of the days in the past\n- Measurement data is only considered up to 3 days into the past\n- Radar data is only considered up to 1 day into the past\n\nThe resulting time-range of `historyDays` and `forecastDays` must contain at least one day."},"latOrStation":{"name":"lat","in":"query","schema":{"type":"number","description":"A Latitude value in degrees (WGS 84) between `-90.0` and `90.0`.","examples":[47.5596],"maximum":90.0,"minimum":-90.0},"description":"Latitude of the location, in degrees (WGS 84). This parameter must be specified if no station ID is provided."},"lonOrStation":{"name":"lon","in":"query","schema":{"type":"number","description":"A Longitude value in degrees (WGS 84) between `-180.0` and `180.0`.","examples":[7.5886],"maximum":180.0,"minimum":-180.0},"description":"Longitude of the location, in degrees (WGS 84). This parameter must be specified if no station ID is provided."},"asl":{"name":"asl","in":"query","schema":{"type":"number","description":"Height above sea level measured in meters.","examples":[0.0],"maximum":9000.0,"minimum":-500.0},"description":"The elevation above sea level in metres for the location of interest. If not specified an elevation is inferred from the given location using an 80 metre resolution digital elevation model (`DEM`).\nSpecifying an elevation can improve forecast accuracy, as the API applies elevation corrections to the returned variables.\nEspecially in complex alpine terrain, the Forecast API behaves different for coordinates in a valley and on the mountain."},"station":{"name":"station","in":"query","schema":{"type":"string","description":"A Station Identifier.","examples":["MLM*API*METEOSCHWEIZ_BAS","MOS*API*METEOSCHWEIZ_BAS"],"minLength":1},"description":"You can provide a station identifier instead of `lat` and `lon`. For some variables, the mLM forecast is optimised using data from the specified station. The requested station must be active and have a sufficient history of high-quality data. Requests for stations that do not fulfil these requirements may fail or produce faulty results.\n\nThe variables being optimised are common weather-station variables like temperature, relative humidity, wind and precipitation and all variables than can be derived from these.\n\n_Access to this parameter is restricted. For more details you can [contact us](mailto:support@meteoblue.com) directly._"},"name":{"name":"name","in":"query","schema":{"type":"string","examples":["name_to_be_returned_in_response"]},"description":"Custom name which can optionally be supplied to be returned in the response. This parameter is returned as is and is not used for any other purpose.\nSpecial characters must be URL-encoded."},"tz":{"name":"tz","in":"query","schema":{"type":"string","externalDocs":{"description":"List of timezones which are included in the Timezone Database.","url":"https://en.wikipedia.org/wiki/List_of_tz_database_time_zones"},"examples":["utc","Europe%2Fzurich"]},"description":"Timezone identifier as specified in the timezone database.\n\nIf no time zone is specified, the API will detect the time zone automatically. For coordinates at sea, the API attempts to determine a nearby coastal time zone (up to approximately 50 km), otherwise `utc` is used.\n\nFor automated systems and further data processing, the use of UTC without local time zone offsets or seasonal time changes is recommended.\n\nFor timezones with daylight saving time, only the time-offset at the time of the API call will be used. There will be no daylight saving time switches in the actual data. So if a place switches from Summertime to Wintertime on Sunday (20.11.2019) and the api is called on Saturday (19.11.2019), all days of the forecasts will use Summertime.\n\nFor time zones with fractional hour offsets (for example, Asia/Kolkata at UTC+05:30), the offset is rounded to a full hour internally."},"timeformat":{"name":"timeformat","in":"query","schema":{"type":"string","enum":["iso8601","timestamp_utc","timestamp_ms_utc","YMD","Y-M-D"],"default":"Y-M-D","examples":["Y-M-D"]},"description":"Specifies the format in which time values are returned."},"format":{"name":"format","in":"query","schema":{"type":"string","enum":["json","csv","xlsx","highcharts","highchartsHtml"],"default":"json","examples":["json"]},"description":"Specifies the format in which the response is returned.\n\n*Note that the CSV format does not support mixing different time resolutions and is not compatible with all packages. Make sure to always parse the header and check the column location of the queried variable, as these positions might change, when new variables are added and this might happen without any communication from meteoblue.*"},"temperatureUnit":{"name":"temperatureUnit","in":"query","schema":{"type":"string","enum":["C","K","F"],"default":"C","examples":["C"],"x-enumDescriptions":{"C":"Celsius","K":"Kelvin","F":"Fahrenheit"}},"description":"Specifies the unit used for temperature values in the response."},"windSpeedUnit":{"name":"windSpeedUnit","in":"query","schema":{"type":"string","enum":["m/s","km/h","mph","kn","bft"],"default":"m/s","x-enumDescriptions":{"m/s":"meter per second","km/h":"kilometer per hour","mph":"Miles per hour","kn":"Knots","bft":"Beaufort"}},"description":"Specifies the unit used for wind speed values in the response."},"windDirectionUnit":{"name":"windDirectionUnit","in":"query","schema":{"type":"string","enum":["degree","2char","3char"],"default":"degree","examples":["degree"]},"description":"Specifies the unit used for wind direction values in the response."},"precipitationUnit":{"name":"precipitationUnit","in":"query","schema":{"type":"string","enum":["metric","imperial"],"default":"metric","examples":["metric"]},"description":"Specifies the unit used for precipitation values in the response."},"domain":{"name":"domain","in":"query","schema":{"type":"string","enum":["NEMS4","NEMS12","NEMSGLOBAL","NEMSIN","NEMSAS02","NEMSAF01","NEMSSA","ICON","ICONEU","ICOND2","GFS05","NAM12","NAM5","NAM3","HRRR","MFGLOBAL","MFEU","MFFR","GEM15","GEM2","MSM","UKMO2","NBM","WRFAMS"],"minLength":1},"description":"Specifies the domain from which the data are retrieved. By default the API uses data from different models and combines them into a single value optimised for the selected location. Specifying a domain overrides the default model selection behaviour.\n\nIn most cases, this parameter should not be set."},"raw":{"name":"raw","in":"query","schema":{"type":"boolean","default":false},"description":"If a raw model forecast is required, this query parameter can be used to request it. By default, data from multiple models are combined, and post-processing techniques are applied to improve data quality.\n\nIn most cases, this parameter should not be set."}},"headers":{"accounting-header":{"schema":{"type":"integer","examples":[0],"minimum":0},"description":"The total number of credits which were accounted from the user of the apikey for the made request."}},"securitySchemes":{"apikey":{"description":"A meteoblue API access key","type":"apiKey","name":"apikey","in":"query"}}}}