NEW! One Call API for essential weather data

NEW! One Call API for essential weather data

OpenWeather is proud to launch a new product, One Call API. By making a single call to this API, you can get access to a set of essential weather parameters for any location on the globe.

Announcement: Radar data in our Weather Maps

Announcement: Radar data in our Weather Maps

Our development team is working on the launch of radar data on precipitation (snow and rain) in the United States.

OPENWEATHER LTD HELPS THE FIGHT TO OVERCOME COVID-19

OPENWEATHER LTD HELPS THE FIGHT TO OVERCOME COVID-19

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.  

New feature in Bulk Downloading: Now you can get bulk files for the previous seven  days

New feature in Bulk Downloading: Now you can get bulk files for the previous seven days

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.

Import OpenWeatherMap Data to Google Sheets

Import OpenWeatherMap Data to Google Sheets

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.

Discover NDVI and its practical uses in agriculture

Discover NDVI and its practical uses in agriculture

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

40 years of weather history is now available without registration

40 years of weather history is now available without registration

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.

Historical collection | Part 2: Historical weather API

Historical collection | Part 2: Historical weather API

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.

Building visual agro service based on weather and satellite data |  Part 2: Satellite imagery

Building visual agro service based on weather and satellite data | Part 2: Satellite imagery

This article is describing the ‘Satellite imagery’ page

Weather Triggers API Part 1 | What is the Weather Triggers API

Weather Triggers API Part 1 | What is the Weather Triggers API

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.

Upgrade of API Multilingual feature. US cities search by states

Upgrade of API Multilingual feature. US cities search by states

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

OpenWeatherMap data in Mozilla's IoT project: WebThings Gateway

OpenWeatherMap data in Mozilla's IoT project: WebThings Gateway

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.

Dive into Agro API | Part 4 – Satellite Imagery

Dive into Agro API | Part 4 – Satellite Imagery

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.

Learn IoT with the OpenWeatherMap API

Learn IoT with the OpenWeatherMap 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.

New! 30 years of historical data from OpenWeatherMap!

New! 30 years of historical data from OpenWeatherMap!

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

OpenWeather 2019: results of the year. Historical weather data,  Weather API, Agro Dashboard

OpenWeather 2019: results of the year. Historical weather data, Weather API, Agro Dashboard

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

NEW! History Bulk and History Forecast  Bulk: choosing any location on the map

NEW! History Bulk and History Forecast Bulk: choosing any location on the map

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

NEW!  ‘Feels like’ temperature in OpenWeather APIs

NEW! ‘Feels like’ temperature in OpenWeather APIs

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

From now on, History Forecast Bulks can be purchased directly on the website

From now on, History Forecast Bulks can be purchased directly on the website

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

Historical collection | Part 1: History API, History Bulk, Statistical API and History Forecast Bulk

Historical collection | Part 1: History API, History Bulk, Statistical API and History Forecast Bulk

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.

History Bulk update! Create your own customised set of weather parameters and units

History Bulk update! Create your own customised set of weather parameters and units

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

NEW! Time Machine: 40 years of historical data for any coordinates

NEW! Time Machine: 40 years of historical data for any coordinates

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

Building visual agro service based on weather and satellite data  I Part 1: Agro Dashboard

Building visual agro service based on weather and satellite data I Part 1: Agro Dashboard

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.

New! History Forecast Bulk

New! History Forecast Bulk

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

Dive into Agro API  | Part 3 -   Historical NDVI

Dive into Agro API | Part 3 - Historical NDVI

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

Dashboard update: Current and historical soil data

Dashboard update: Current and historical soil data

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

World Observation Business Week in Paris

World Observation Business Week in Paris

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

We have integrated time zones into our weather API products!

We have integrated time zones into our weather API products!

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

Dashboard update: Accumulated parameters and weather history

Dashboard update: Accumulated parameters and weather history

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

Visualisation of the NDVI index on satellite maps. Custom palettes for agricultural applications

Visualisation of the NDVI index on satellite maps. Custom palettes for agricultural applications

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

Statistical Weather Data API is now available!

Statistical Weather Data API is now available!

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

Climate API: Climate forecast for 30 days

Climate API: Climate forecast for 30 days

We are glad to introduce our users to a new product which is based on a statistical approach to our historical weather data.

The second version of our updated Dashboard: Weather data!

The second version of our updated Dashboard: Weather data!

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

Our new weather product – Hourly Forecast!

Our new weather product – Hourly Forecast!

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


The first version of our updated Dashboard!

The first version of our updated Dashboard!

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

Our team is actively developing a new version of the Agricultural Dashboard!

Our team is actively developing a new version of the Agricultural 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.

Data from Modis on the VANE platform!

Data from Modis on the VANE platform!

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 – #1: Description of products

Weather Map 2.0 and Relief Maps – #1: Description of products

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. 

How to move from Weather Underground to OpenWeather

How to move from Weather Underground to OpenWeather

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.

OpenWeather 2018: Results of the year: Agricultural, Satellite imagery and Weather API

OpenWeather 2018: Results of the year: Agricultural, Satellite imagery and Weather 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.

The OpenWeather team announces Relief Maps!

The OpenWeather team announces Relief Maps!

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!

The OpenWeather team announces Weather Maps 2.0!

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!

Dashboard for Agricultural Monitoring

Dashboard for Agricultural Monitoring

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).


Satellite imagery API: Why Satellite imagery API?

Satellite imagery API: Why Satellite imagery API?

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.

Query Builder Palette

Query Builder Palette

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.

How to get free satellite imagery from Sentinel-2

How to get free satellite imagery from Sentinel-2

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.

Dive into the Agro API | Part 2 – Polygons

Dive into the Agro API | Part 2 – Polygons

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.

How we process satellite imagery so that you can operate with ready-to-use data

How we process satellite imagery so that you can operate with ready-to-use data

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).

Dive into the Agro API | Part 1 – Personal account

Dive into the Agro API | Part 1 – Personal account

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.

Satellite Images API for Agriculture: NDVI, EVI, True and False colour

Satellite Images API for Agriculture: NDVI, EVI, True and False colour

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.

Weather and satellite APIs for precision farming

Weather and satellite APIs for precision farming

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.

NEW! Agro API – service for agriculture

NEW! Agro API – service for agriculture

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.

VANE platform: The Polygon tool

VANE platform: The Polygon 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.

VANE platform news

VANE platform news

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

OpenWeatherMap 2017: Results of the Year

OpenWeatherMap 2017: Results of the Year

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!

Cloudless: global cloudless composite coverage based on the VANE platform

Cloudless: global cloudless composite coverage based on the VANE platform

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.

Weather widget’s new geolocation and weather map functionality

Weather widget’s new geolocation and weather map functionality

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 Query Builder web interface for our VANE platform

You are invited to test the new Query Builder web interface for our VANE platform

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.

The influence of temperature on plant productivity in agriculture: Accumulated temperature

The influence of temperature on plant productivity in agriculture: Accumulated temperature

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.

New API for accumulated temperature and precipitation data!

New API for accumulated temperature and precipitation data!

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.

Accumulated precipitation data for agriculture

Accumulated precipitation data for agriculture

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.

Accumulated temperature data for agriculture

Accumulated temperature data for agriculture

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 significant improvements in one of our products – API for UV-index

We are happy to announce significant improvements in one of our products – API for UV-index

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.

We have extended the list of supported languages for weather conditions

We have extended the list of supported languages for weather conditions

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.

New styles for Weather Maps API

New styles for Weather Maps API

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}

History Bulk documentation

History Bulk documentation

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.

Weather Historical Bulk is launched!

Weather Historical Bulk is launched!

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.

How to know what particular imagery you get from the VANE Geospatial Platform

How to know what particular imagery you get from the VANE Geospatial Platform

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.

Weather alerts from OpenWeatherMap

Weather alerts from OpenWeatherMap

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.

Satellite imagery: Landsat 8 and its Band Combinations.

Satellite imagery: Landsat 8 and its Band Combinations.

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.

Weather Stations API 3.0

Weather Stations API 3.0

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.

How to use OpenWeatherMap UV Index

How to use OpenWeatherMap UV Index

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 the VANE Language service

OpenWeatherMap presents the release of the VANE Language service

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.

Map Editor 2.0: Map with bike routes

Map Editor 2.0: Map with bike routes

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!

                    

                


Map Editor 2.0 – the newest version of our tool for customising weather maps

Map Editor 2.0 – the newest version of our tool for customising weather maps

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!

Air pollution: ways to forecast and calculate it

Air pollution: ways to forecast and calculate it

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.

New air pollution APIs

New air pollution APIs

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.