Our API takes the name of any global location or zip code, and converts it into a list of coordinates (known as direct geocoding) as well as converting a geolocation into a list of place names (reverse geocoding).

The everpresent food delivery rider is now just as an intrinsic part of our urban lifestyle as our internet connection...

There are countless ancient, yet rather dubious sayings about our weather ....

The Secret Ingredient For a Sustainable Wine Industry

How to shed light on your energy needs with the OpenWeather Solar Radiation API Historical data

Visual global agricultural data in less time than a raindrop takes to fall to earth.

The fruity future of wine.

Keep ahead of the conditions with the OpenWeather Road Risk API update.

Bring some shine to your app with our Global Solar Radiation Forecast and Current data API.

Introducing the Weather Maps 2.0 with 1-hour step - a visual and feature-rich API that gives you weather map tiles for any global location.

OpenWeather have introduced their Global Precipitation Maps - Forecast and Historical data API that offers data with just a ten minute step, and US forecasts for the next six hours.

Introducing the OpenWeather History API Full Archive - up to 40 years of detailed weather data for any specified global location.

Introducing the OpenWeather History API by Timestamp that gives detailed weather information for any specified global location and time over the last 40 years.

Test summary

You can now personalise your iPhone Home Screen with the widgets from OpenWeather App - one widget is for current weather and the other one is for the short-term forecast for 4 hours. The weather data from OpenWeather can now be delivered right on the screen of your phone, withdrawing the need for swiping left and right while searching for the app icon.

The granularity of the UV index has been increased and it is now included into the One Call API. In case you are using the preceding API for UV index, we would encourage you to switch to the enhanced solution.

In OpenWeather we have an annual tradition of drawing the results of the year. The year 2020 was not easy for all of us. The unparalleled healthcare challenge has unveiled the fragilities of our world and OpenWeather sees its mission in making a positive change. The current crisis created a momentum where everyone can make a change towards a better climate, cleaner air and a sustainable future.

In this article, we explain why weather must be taken into account when modelling the spread of COVID-19, which specific parameters are thought to be most significant, and everything we are doing to help in this collaborative, worldwide research effort.

The Air Pollution API can facilitate the urban planning and the abatement of traffic congestion. Our quality data makes the sustainability goals achievable for your business. The Air Pollution API provides current, forecasted and short term history data on the concentration of  CO; NO; NO2; O3; SO2; PM2.5; PM10 and NH3 in the air for any location around the World. It is included into all the OpenWeather subscriptions, starting with the freemium plan.

We are happy to announce that students and educators can now use our Medium plan for historical weather collection and Developer’s plan for current weather and forecasts absolutely free. We have previously granted access to weather data for researchers studying COVID-19, which resulted in a fruitful collaboration. In OpenWeather, we are dedicated to fostering the interest in data-science and climatology, and this exclusive student offer is purposed to facilitate the access to weather data.

Global Weather Alerts brings simplicity into working with national weather alerts on the Global scale. It streams the accumulation of current alerts into your IT system in a standardised and unified format. The full description of the alert includes such parameters as: coordinates of the area affected; alert category; urgency; start and end time etc. You don’t need to specify any location parameters. All the National Weather Alerts are delivered to you immediately upon its issue in a neat JSON packaging.

The ad-free & free-to-use OpenWeather App arrives to the App Store this week. The application is here to seize the entire potential of our One Call API, the amalgamation of minute-by-minute forecast for 1 hour; hourly forecast for 2 days and daily forecast for the week, along with national weather alerts. The pinnacle of weather API’s is now brought right onto your mobile device.

OpenWeather delivers Road Risk API as a humble contribution towards sustainable transportation. Enhance your short-term planning with Road Risk API by exploiting an accurate minute-by-minute forecast for 2 hours, hourly weather forecast and national alerts for five-days. The weather data is provided for any moment of time for 5 days ahead and 5 days back, covering any destination and any point along the route.

Our freemium service for One Call API is now augmented with government weather alerts. All essential weather data you need is available in one place through our One Call API.

Obtain your weather data with the Climate Forecast for 30 days API and plan your journey through the month. The fusion of know-how and plethora of historical meteodata will make the weather work for you.

We keep improving our weather products! This time, we are happy to tell you that we have added the Probability of precipitation parameter to our weather forecasts.

From temperature-driven customer desires to delays in supply chains, weather impacts the retail industry in a significant way.

Some of us might wonder how accurate the forecast is, and why it is constantly changing. We at OpenWeather use our own tools to monitor accuracy and quality metrics, to make sure we provide better data to our customers through our API.

Weather data should be open to everyone. Above all other types of data, the weather is the most critical to our daily lives. Since everyone can benefit from it, weather data shouldn't cost a lot of money at all.

Adding weather data to your exercise app is a sure-fire way to create a more immersive user experience. Whether your app focuses on running, cycling, or other sports, there's a good chance the weather outside plays a big role in your users' motivation and performance.

History Forecast Bulk is an archive of data on previously made 16-day forecasts collected from 7 October 2017 onwards, and available for any coordinates on the globe.

The API to provide accumulated temperature and precipitation is part of the functionality of our APIs for the agricultural sector. Accumulated temperature and precipitation are calculated based on historical weather data, and play a fundamental role in agricultural productivity.

Historical weather data are used in various areas of the economy and industry. They allow you to assess the impact of weather on business, are used to analyze and reduce potential risks, in machine learning, in the IoT system and much more.

We are happy to introduce our new product – Historical Weather Data by State for all ZIP codes, USA.

The transportation industry, both in itself and as a part of logistics, is highly dependent on short-term weather events.

History Bulk is a one-time export of historical weather data going back up to 40 years. You can choose any period of time from 1 January 1970 until now for your order.

Getting historical weather data for a large number of locations at once

Today we have added historical weather data to our One Call API. Apart from current and forecasted data, now you can also request historical weather data for 5 previous days.

OpenWeather offers a great solution to users who have been affected by the closure of the Dark Sky API.

We're proud to officially announce the launch of One Call API. This powerful and affordable weather service allows you to retrieve current, historical, and forecasted weather data in just one request, making it the ideal integration for a wide range of use cases.

During these unprecedented times we want to contribute and help companies that analyse data corresponding to research to help find a cure towards the battle of Covid-19. We want to provide you with free access to historical weather data to help support the fight at completely no cost to yourselves.  

We have added new functionality to Bulk Downloading. The main idea of this product is to allow you to regularly download batches of current weather and forecast data for more than 200,000 locations at once via a JSON file.

We are often asked how to import weather data from the OpenWeatherMap API directly into Google Sheets. To help you with this, we would like to refer you to the detailed guide “Import OpenWeatherMap Data to Google Sheets”, written by Mixed Analytics.

Quite often we receive questions like what NDVI is, how to use it and why would a farmer require using it at all.

OpenWeather is proud to announce the weather archive has expanded to 40 years dating back from 1st Jan 1980. The new order form is now available on the ‘Marketplace’ page.

The Historical weather API is designed to provide hourly historical weather data for more than 37k cities with basic parameters: Temperature, Pressure, Humidity, Wind, Precipitation and Clouds.

This article is describing the ‘Satellite imagery’ page

The Weather Triggers API is a flexible tool, which allows developers to set trigger conditions and provides possibility for end-users to monitor trigger execution in real-time.

The OpenWeather team has made two important updates this month in the Current weather data product. Hope, you’ll enjoy more user-friendly experience.

Our Current weather data are participating in a new Mozilla project The WebThings Gateway for home automation: Monitor and control all your smart home devices via a unified web interface.

The Satellite Imagery API is a part of our Agriculture API (Agro API) for the agricultural sector. OpenWeather provides satellite data for user-defined polygon in the format of images in true colour, false colour, NDVI and EVI indices, and of NDVI and EVI statistical data. To obtain them we suggest using our Satellite Imagery API.

It is well known that OpenWeatherMap weather project products from OpenWeather are particularly popular with students and novice developers. Which is not surprising: the availability, ease of use and convenience of our products are some of the major principles of OpenWeather.

A new depth of historical data that is available through your personal account has been increased from 19 to 30 years!

So, the new 2020 is nearly upon us and it is time to sum up what we have done in 2019.

There is a new update available for our historical data service.

We have added “Feels like” parameter.  This parameter accounts for the human perception of weather; it lets you know how the temperature “feels”.

For your convenience, we have significantly simplified the procedure for obtaining this data.

Today, we would like to tell you more about one of the most requested weather services from OpenWeather - our Historical weather data. It is based on our new “Time Machine” weather technology.

OpenWeather team is pleased to announce some exciting news for our History Bulk users!

OpenWeather team is glad to present a new technology that greatly enhances our historical weather data. We have called it Time Machine.

OpenWeather is delighted to offer fast and simple APIs for both weather data and satellite imagery. 

Specifically for agro-users, we have selected a set of APIs that can be incredibly useful for work in the context of agricultural digital solutions development. Additionally, we offer more specialized  APIs as well.

The OpenWeather team is pleased to announce the launch History Forecast Bulk!

Historical NDVI API is a part of an overall functionality of Agro API, a digital tool created for the needs of agricultural users.

The OpenWeather team is pleased to announce that we continue to expand the functionality of our Dashboard.

OpenWeather participated in one of the most significant conferences in the industry - World Observation Business Week in Paris

The OpenWeather team is pleased to inform you that we have successfully integrated time zones into our weather API products.

The OpenWeather team is pleased to inform you that once again we have significantly expanded the functionality of our Dashboard

For developers of agricultural services or applications, we offer several predefined color palettes.

Statistical Weather Data is an API that can provide its users with aggregated statistical weather data for cities.

Now you can use our Weather Data function, in addition to those that are already implemented in the Dashboard.

The OpenWeather team is pleased to present you our new product, Hourly Forecast.

We are pleased to tell you that we have launched the first version of our updated Dashboard!

The main purpose of this significantly advanced version of the Dashboard is to visually demonstrate to you all the data that we provide in our Agricultural API.

The OpenWeather team is pleased to present a new source of current data for the VANE platform service – two Modis satellites: Terra and Aqua.

Weather Map 2.0 and Relief Maps are products that allow developers to add weather and relief maps to their applications using simple URL requests. 

OpenWeather will help you easily and quickly move to our Weather API if you have been affected by the closure of the Weather Underground API.

So, the new year 2019 has come and it’s time to sum up the results of the past year for our company, OpenWeatherMap, provider of one of the best weather APIs in the world.

Relief Maps allows you to get relief maps from around the world. Set the position of the sun in your parameters and you will receive precise illumination of the earth’s surface and its relief for the conditions you have set.

The OpenWeather team announces Weather Maps 2.0, where you can now work not only with current weather layers but also with historical and forecast maps!

The Dashboard for Agricultural Monitoring is a service created for visual demonstration of satellite data (NDVI) and weather data (forecast, historical and accumulated parameters), which you can get for your area of interest (that is, for your polygons).

In the past, it was not easy to work with satellite imagery and use the images in applications. You had to have deep expertise in the satellite imagery area and have access to massive computing capacity. Fortunately, now this data is available in a much easier way through our APIs.

When you work with single-channel images, you need to focus in depth on a narrow range of values and clearly evaluate the researched data.

If you want to download Sentinel-2 satellite data, you’ve come to the right place! Our Satellite Images API was created exactly for this purpose.

This article is a step-by-step description of how to work with polygons using our QueryBuilder and Agro API instruments. Part 1 explained how to use your personal OpenWeather account – be sure to set it up before starting to read this article.

1) Satellite data search.
1.1. Selection of suppliers or distributors of satellite data.
1.2. Data search in archives. Search is based on the following criteria: date of satellite imagery, percentage cloud coverage, type of satellite imagery system, level of data preprocessing, geographical area of interest (AOI).

This April, OpenWeather presented a brand new product, the Agro API, which was intended to change the working process of agricultural applications. Our algorithms for collecting and processing satellite scenes and weather data, combined with the simplified delivery of prepared products to the end user, make this product wholly unique and very convenient.

In this article, we would like to look in more detail at one of the essential elements of our Agro API: the Satellite Images API. The Satellite images API is the dataset from the Landsat 8 and Sentinel-2 satellites on the basis of which we calculate quantitative indices, such as NDVI, EVI and others, and from which we also obtain ready-made images of territories in True and False colour, NDVI and EVI.

We provide historical data as well as satellite images that are as up to date as possible (allowing for the data source and cloud cover) for the very nearest time period. These images are available to all account users, including those who are using the free package. For non-paying users, the range for satellite data requests is 6 days. For the paid service, it is one year. You can learn more about our pricing plans here.

Please note that there are limits to the total area for which you can request data, and to the number of requests that you can make per minute. However, should you exceed these figures, we will continue to provide you with the data you need so that your work is not affected and your customers will not run and hide!*

You can find all the details and the full set of the Agro API‘s capabilities here.

As always, we would be glad to hear your comments and suggestions regarding our product!

* At the end of your billing month, we will provide you with a separate bill for any additional area, beyond the tariff limits, for which you requested data.

Objectives

As farms mainly consist of crop fields, which can be hundreds of acres in size, much time and a great deal of resources are demanded of farmers in obtaining an accurate picture of the overall condition of these farms.

Drying out of plants or, conversely, an excess of moisture and a rise in the number of pests: these can all take their toll on the size and quality of the harvest and demand a rapid response. There are also such problems as the danger of overusing fertilisers, which poses a threat not only in terms of extra costs but also in that it is harmful to the environment and primarily to the health of farmers themselves.

To maximise harvests, constant monitoring is required throughout the season; and it is not easy finding the time to keep up with changes for each crop, not to mention monitoring the condition of every single acre. When deciding on long-term plans, a comparative analysis has to be carried out for both the usual course of the seasonal cycle and, in particular, any crises that have arisen.

To assess the current situation and to keep track of changes compared with preceding seasons and with the condition of neighbouring fields, accurate information on both the past and the present is needed as well as future forecasts that are as precise as possible.

Solutions

There are currently numerous services that help with managing farms for any acreage: checking boundaries and nutrient and moisture intake, monitoring the negative effects of weather conditions and diseases, and controlling pest numbers. And this can all be done without having to visit the fields, just by using a phone or tablet screen or a PC.

It is exactly to provide these services that OpenWeather offers a wide range of APIs for different weather and satellite data combined in the one product, the Agro API, with universal and simple syntax.

The OpenWeather team are pleased to announce that we are launching a new product aimed primarily at specialists developing agricultural services and addressing the specific requirements of this sector. This product is also geared toward the insurance and banking sectors and can be used as a farm rating tool.

An example of one of the services for agricultural applications offered by VANE has now been added to the Query Builder interface.

The Polygon tool allows you to isolate any outline you want in the photograph, process the satellite images in RGB and EVI, and arrange any colour palette with any scale for a specific area.

It is possible to edit it, obtain data on the depicted polygon and download it from the GeoJSON file.

You can then get the URL with the assembled polygon and copy it to your site.

The filter algorithm for selecting BEST coverage tiles has changed.

BEST is the method for overlaying images (parameter value order), and is the best way possible, depending on the parameters selected: date range, satellite, percentage cloud cover.

Changes to the algorithm have enabled the quality of coverage to be significantly enhanced:

Sentinel-2 - before

Sentinel-2 - after

– combined data sources Landsat 8 and Landsat 8 TOA.

Landsat 8

Landsat 8 + Landsat 8_TOA

So the, new year, 2018, has come, and it’s time to sum up the results of the past year for our company, OpenWeatherMap (UK, US and Latvia), developers of one of the best weather APIs in the world. A lot has happened and much has changed.

During the year, our number of users grew from 600,000 to 1 million. We participated in the Startup Grind Global Conference in Silicon Valley, where the team from OpenWeatherMap was named in the top 50 Startup Exhibitions of 2017. Our mature team was filled up with excellent professionals and wonderful people.

We did a lot of new things and qualitatively improved our current developments. In 2017, we were pleased to present to you:

Weather data: API and Weather Maps

• The Open Dashboard for Agricultural Monitoring can help give you an idea of the possible use for meteorological and satellite data in your agricultural applications.
• Specially for the agriculture sector, we launched an API for accumulated temperature data and another for accumulated precipitation data.
• The Weather Historical Bulk service. Now you can simply choose a city/town (or several cities/towns) and download an archive, which contains a bulk file with the weather history for up to 5 years – any day or week, or even several years.
• A new and improved version of an API for UV-index.
• Throughout the entire year, we worked constantly on our history weather API. During the year, the amount of data supplied and the speed of processing that data increased significantly. Also, we made it possible to quickly upload data in a format that doesn’t require additional processing and can be understood by any user.
• Our Weather Maps app changed qualitatively in 2017. We added the ability to switch the layers of weather and satellite maps, create various combinations with them, and connect them to mobile and web apps.

Satellite data: VANE platform

In 2017, we significantly improved our satellite platform. Our team undertook a huge amount of work and in June were able to present a new version of the satellite image processing platform VANE.

Based on the VANE platform, we developed a new product called Global Satellite Base Map, which uses visual tools and query language to generate a map from satellite images. The uniqueness of the product is that all data processing is done on the fly, and there are no presets or pre-made calculations. The user defines the parameters for a calculation and image processing and immediately receives a result for any territory. This capability was only possible thanks to VANE, our super-powerful data processing platform.

We recently presented you with Query Builder, our new interface for the VANE platform. Now you can use this simple tool to create your own map in just a few seconds, and with just one click receive a completed link for display on your site or app using a web map library like Leaflet, Open Layer, Mapbox and Google Maps.

We are grateful to everyone that worked with us for all this time. We thank you for all your feedback and for not getting bored by our tech support.

We have a ton of plans for the coming year. Stay tuned, and you will see a lot of the new and interesting things to come. Subscribe to our Telegram Channel https://t.me/openweathermap and get news first about our updates and new products!

The drawings show global coverage obtained between 1 June 2017 and 1 September 2017 using data from the MODIS spectroradiometer aboard KA Terra and Aqua.

The current cloudless coverage of the Earth by medium and low-resolution satellite images is an important element in the regional and global systems that monitor the territorial changes caused by natural and man-made factors. For example, assessing the damage inflicted by forest fires caused by deforestation, volcanic eruptions, flooding and so on. Also, such types of coverage are popular as the base layer for cartographic web services.

The main stages of creating such coverage are: the selection of images, the masking of clouded areas, tonal adjustment of images taken at different times of the year, and pasting them into single coverage using so-called “cutlines”, which enable, to a certain extent, the joins between the pasted images to be hidden. Such operations, as a rule, are carried out in semi-automatic mode and require specialised software and highly qualified experts, which substantially increases both the time taken to create such a product and its cost.

We invite anyone wishing to do so to try out our weather widget’s new geolocation and weather map functionality – https://openweathermap.org (please note that ‘https://’ is required in the URL), which can be targeted to your specific location.

You are invited to test the new web interface Query Builder for our Vane platform.
You can use this simple tool to create your own map in just a few minutes, and with just one click receive a completed link for display on your site or app using a web map library like Leaflet, Open Layer, Mapbox and Google Map.

This version is an improvement over the previous one in terms of simplicity of use and layout. The user can select either one of the available data sources and the required combination of spectral bands or one of the derivative index products such as NDVI, EVI, etc. You can also set up display parameters, including clarity, contrast and gamma correction, or use one of the available schemes provided. After that, all you need is to get an API key and insert it in the prepared link, and you can use it in your programming product.
We are ready to answer your questions and will be glad to hear any proposals you might have.

Accumulated temperature is a weather parameter that directly influences the productivity of agricultural plants. All biological and chemical processes taking place in the soil are connected with air temperature. The heat supply of crops is characterised by a sum of average daily air temperatures that are higher than a biological minimum during a vegetation period. Both too-high and too-low temperatures spoil the course of biochemical processes in cells, and irreversible changes can be caused that lead to a stoppage of growth and the death of plants.

We are happy to announce our new APIs based on historical data and focused primarily on users from the agricultural sector – API for accumulated temperature data and API for accumulated precipitation data.

Accumulated temperature data is an index that denotes an amount of warmth. It is determined as a sum of average daily air and soil temperatures that exceeds a defined threshold of 0°C, 5°C or 10°C, or a biological minimum temperature level that is crucial for some specific plant.

Accumulated precipitation data is calculated as a sum of all parameters for a particular period.

Precipitation, mostly rains, has a huge impact on agriculture. For plants to grow, they need at least a small amount of water, and rain is still one of the most effective ways of watering despite the development of modern technologies.

Too much or too little precipitation is bad and even harmful for agricultural plants. Drought can destroy the harvest and increase erosion, and overly humid weather can trigger the growth of unfavourable fungi. Also, different kinds of plants demand different amounts of precipitation. For example, some succulent species require little water, while tropical plants need hundreds of inches of rain a year just to continue living.

The fluctuation in precipitation amounts is quite substantial in continental climates. They fluctuate more in a month than during a year. A considerable variation in precipitation leads to situations where drought takes place during the years with low amounts, thus forming areas of unstable hydration. With a long absence of rains and at high temperatures, the reserves of moisture in the soil dry out due to evaporation.

A previous arid season brings a shortage of crop yield even in a humid season, as the harvest lacks enough time for ripening. Thus disadvantageous conditions for ordinary plant development are established, and the crop yield of agricultural plants decreases or perishes.

Along with precipitation amounts, the number of days with precipitation in a month or a year is also a significant climatic index. Plants are sensitive to whether a given precipitation amount falls all at once during just a few days, or it rains often and the amount is distributed comparatively evenly throughout a month. For instance, even one great downpour in a prairie area in summer has little ability to improve an arid situation.

By employing a data set of precipitation amounts and a number of days, one can calculate an accumulated precipitation amount for any region during a specific period of time.

Temperature, and especially accumulated temperature, is an important factor and plays a fundamental role in agricultural productivity. Plants and insects develop in accordance with the temperature. The warmer the weather, the faster they grow and reproduce; the colder it is, the more slowly these processes go.

All species have a biological minimum temperature level, below which development does not take place at all. When the temperature of the environment begins to exceed this minimum level, it gives a start to growth and reproduction. The value of this basic temperature (or a development threshold) has a crucial significance, and it differs between species of plants and insects.

Accumulated temperature (AT) represents an integrated excess or lack of temperature in relation to a fixed starting point. This index is calculated as the sum of the average daily temperatures of air and soil, above a chosen threshold of 0°C, 5°C or 10°C, or a biological minimum temperature level.

Basically, this is a way of including temperature and time into one dimension for quantitative evaluation of the speed of growth of plants and insects. Usually the index of accumulated temperature data is used to create models of crop growth.

In the near future, we will introduce our new API for accumulated temperature data. It will be based on historical data, and will be focused primarily on users in the agricultural sector.

We are happy to announce that one of our products – API for UV-index – has been significantly improved.

• Now, as well as current and historical data, you can also get UVI forecasts for periods of 8 days.
  
• The syntax has been made considerably easier: it has become clearer and more unified, like other API versions.
  
• There is a new feature to request data for any geographic coordinates without limits on accuracy.
  
• The accuracy level of the UVI modelled data has been doubled (the interpolation grid step has been reduced from 0.5 to 0.25 degrees).  
  
• Soon, searching by city/town name, city/town ID and postal/ZIP code will be available.

You can find the instructions for the updated version at http://openweathermap.org/api/uvi.

Access to the UV-index data will be available for all our plans. For more information on our plans, please visit http://openweathermap.org/price.

The previous version of the API (http://openweathermap.org/api/old-uvi) will soon be announced as deprecated, and no further support will then be provided for this version.

Do you want to receive weather data in your language? We have extended the list of supported languages for weather conditions.

Now the following languages are available in our API:

Arabic (ar); Czech (cz); Greek (el); Persian (Farsi) (fa); Galician (gl); Hungarian (hu); Japanese (ja); Korean (kr); Latvian (la); Lithuanian (lt); Macedonian (mk); Slovak (sk); Slovenian (sl); Vietnamese (vi).

We invite our users to test translations for weather conditions in different languages. We will be happy to extend our language support according to your wishes. If you have any questions or suggestions, please send them to https://openweathermap.desk.com/. The specification for all weather conditions is available here: http://openweathermap.org/weather-conditions.

We have added new versions of the rendering styles for the Weather Maps API.

To get the weather map layers in the new predefined styles, you need to add _new to the appropriate layer name, as follows:

http://tile.openweathermap.org/map/{layer}_new/{z}/{x}/{y}.png?appid={api_key}

For your convenience while working with our historical data, we have created the History Bulk section at OpenWeatherMap.com. There you can find a manual on extracting data for different time periods and cities/towns; there are also examples of data extraction in JSON and CSV file formats, and descriptions of weather parameters.

We are happy to introduce to you our new service that provides historical weather data for more than 30,000 cities/towns for the last 5 years.

Now you can simply choose a city/town (or several cities/towns) and download an archive, which contains a bulk file with the weather history for up to 5 years – any day or week, or even several years. Pricing is simple and easy – just $10 for one city/town, no matter how much data you receive – see http://openweathermap.org/price.

Just sign in and place an order on your personal page at https://home.openweathermap.org/history_bulks/new. Please note that our traditional History API stays the same.

One of the benefits of the VANE platform is that there is no need to search by scenes and footprints. It is based on a simple assumption: each location in the world has metadata – click on any location and you can get information about all pixels containing this location.

Such projects as cloudless atlases and Google base satellite maps are created according to this basic principle, stitching the best imagery pixels in one seamless mosaic. Based on the scene’s metadata, VANE can choose the best satellite cover – you need to set up a parameter “order=best” for this operation.

As well as this, the VANE language allows you to set up further requirements for your mosaic, providing appropriate parameters in your query:

no older than (“day>{yyyy-mm-dd}”)

or put all the latest imagery on the top (“order=last”)

or within a specific time interval (“between({yyyy-mm-dd}:{yyyy-mm-dd})”).

Then you can go further, applying your custom colours to the result mosaic, according to the VANE language specification.

Just to demonstrate this principle at work, we’ve launched a very basic application called Finder.

We invite you to try our new product, Weather Alerts – it provides weather alerts based on our meteorological data.

Now you can use simple syntax to create triggers, which will work upon the occurrence of specified weather conditions (temperature, humidity, pressure, etc.) in a certain period of time. For example, if you are interested in forecasts of the approach of frosts or the probability of strengthening of wind in a certain place, you can get this information by using our new tool.

The alerts will be generated in our service when the conditions for the trigger are satisfied. You will need to poll the service within a certain time interval in order to receive them. For the future, we are planning to improve and develop this service, with the addition of push notifications and new data sources.

You can find out more at http://openweathermap.org/triggers.

Weather Alerts structure: http://openweathermap.org/triggers-struct.

In the current version of the VANE Language, we use images from the Landsat 8 satellite, which captures the Earth’s entire surface every 16 days. The satellite makes hundreds of images, with a unique name for each one (such as “LC81410552016219LGN00”) and a pixel size of 30 metres. Each image consists of 11 bands; the size of an uncompressed image is 2 GB.

Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images consist of nine spectral bands with a spatial resolution of 30 metres for Bands 1 to 7 and 9. New Band 1 (ultra-blue) is useful for coastal and aerosol studies, and also new Band 9 is applicable for cirrus cloud detection. The resolution of Band 8 (panchromatic) is 15 metres. Thermal Bands 10 and 11 provide more accurate surface temperatures and are collected at 100 metres. The approximate scene size is 170 km north–south by 183 km east–west (106 by 114 miles).

By default, we get Bands 2, 3, 4, 5 and 7, but it is possible to download any other bands.

OpenWeatherMap is happy to announce good news for owners of private weather stations! We are launching a new version of Weather Stations API 3.0. Now there are more easy ways to manage your stations and transmit their data.

Thank you to Francesco Azzola for the article:
– http://www.survivingwithandroid.com
– @survivingwithan
– https://it.linkedin.com/in/francescoazzola

This post describes how to use OpenWeatherMap UV Index. This is an interesting API because we can use it to explore some important aspects of Android and of location-aware APIs. OpenWeatherMap provides this API for free! As you may already know, OpenWeatherMap also provides a full set of APIs about weather information: you can get current weather conditions, forecast, historical information and so on. This information is free, and we can use OpenWeatherMap APIs free of charge.

At the end of this article, we will build an Android app that gets the UV index and shows it using Material Design guidelines.

Before diving into the details of the app, it is useful to have some idea about the UV index.

OpenWeatherMap presents the release of a new service – VANE Language (formerly Imagery API) – with examples here: http://owm.io/vaneLanguage.

We initially called this service the “Imagery API”, but later realised that it consists of much more than just API calls. “VANE Language” is a more appropriate name for it, as it is like an SQL for satellite images. It is a unique offering in the satellite market. VANE Language is an entirely online service – there are no manual procedures, or presets such as maps prepared in advance.

Each “image” that we receive from Landsat 8 is not an image as commonly understood, but several layers that have to be processed and merged in some way before you can do anything with them. Each unarchived number of bands occupies around 2 GB of storage, and it obviously takes a lot of resources and time to process it. For example, to create a global map you need around 10,000 images that need to be processed and merged.

With VANE Language, the developer does not worry about time-costly pre-processing, because we do it all online immediately. We provide a powerful tool that will be familiar to any developer and hides all the complexity. In short, VANE Language gives full flexibility for a developer to do whatever they want with images and deploy the results into applications.

It also has a unique feature: configuring the formula for image processing. This allows the developer to set up their image-processing logic to create specific vegetation indexes, false colours and any other images that they want to use for analysis of objects, changes, yield health, etc.

There are many online map services for those who prefer active leisure. For example, here is a map with bike routes: http://www.thunderforest.com/maps/opencyclemap/.

Route maps are extremely useful! Also, while choosing a route it would be beneficial to know the weather in the region you will be travelling in. And what if we combine a bike route map with weather data from OpenWeatherMap? Eureka!

Map Editor 2.0 can help us with that!

We at OpenWeatherMap are happy to announce our new useful, smart tool: Map Editor 2.0! It allows you to create personalised weather maps on the basis of OpenWeatherMap’s data. Map Editor 2.0 provides a great variety of interface tools: for example, you can choose particular weather phenomena and adjust the colour display. And, as usual, all these tools are available through open access. To get this tool, simply log in to your account or create one. Be ready to become a weather pro!

In recent years, the fight against air pollution has become global. Humanity, at least when we are speaking about developed countries, starts to realize finally that the Earth is our common home which can get not suitable for living in the near future. Atmospheric pollution takes place when substances harmful for living creatures diffuse throughout the surrounding air, and then this destructive activity has its toxic impact later since it causes global changes of climate of the Earth.

Taking into account the great importance of the climate change issue, we at OpenWeatherMap would like to make our own contribution to making this world a better place.

The first version of the APIs includes several data sets: CO (carbon), NO₂ (nitrogen dioxide), O₃ (ozone), SO₂ (sulphur dioxide).

We hope that the air condition data, both current and historical, will give you a great opportunity to create a variety of new applications and analytic services to keep an eye on what we breathe in real time and whether there is any improvement over time.