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- 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 of 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 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 an API for accumulated precipitation data.
• The Weather Historical Bulk service.
  Now you can simply choose a city (or several cities) and download an archive, which contains bulk file with the weather history up to 5 years - any day, 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. For this year, the amount of data supplied and speed to process 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.
  This year, 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

This year, 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 Map.

We are grateful to everyone that worked with us for all this time. We thank you 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!

In the drawing is global coverage obtained between 06.01.2017 and 09.01.2017 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 are 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,etc. 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, expert as a rule, 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 specialized 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 in the URL is required), which can be targeted to the user’s 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 which directly influences productivity of agricultural plants. All biological and chemical processes taking place in the soil are connected with air temperature. Heat supply of crops is characterized 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 a course of biochemical processes in cells, and irreversible changes can be caused that lead to a stop of growth and death of plants.

We are happy to announce our new APIs based on historical data and focused primarily on users from the agro-sector. API for accumulated temperature data and API for accumulated precipitation data.
Accumulated temperature data is an index that denotes an amount of warm. This index is determined as a sum of average daily air and soil temperatures which exceeds a definite threshold of 0, 5, 10 degrees or a biological minimum of temperature level which is crucial for some specific plant.
Accumulated precipitation data is calculated as a sum of all parameters for a peculiar period.

Precipitation, mostly rains, has a huge impact on agriculture. For the growing all the plants need a smallest amount of water at least, and rain is still one of the most effective ways of watering despite the development of modern technologies. Too much or otherwise too little precipitation is bad and even harmful for agricultural plants. Drought can destroy the harvest and can increase erosion as well as the overly humid weather is able to trigger a growth of unfavorable fungi. Moreover, various 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 maintain their living.
A fluctuation of precipitation amounts is quite substantial in continental climates. A fluctuation of month amounts is bigger than those of year. A considerable precipitation variation leads to situations when there is a precipitation lack during some years, and drought takes place thus forming the 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 a crop yield even in a humid season as the harvest lacks time to ripen. Thus disadvantageous conditions for an ordinary plant development are established, and a crop yield of agricultural plants decreases or perishes.  
Along with precipitation amounts, the number of days with precipitation a month or a year is also a significant climatic index. Plants are sensitive about a matter whether a given precipitation amount falls at once during only several days or it rains often and a precipitation amount is distributed comparatively evenly throughout a month. For instance, even one great downpour in a prairie area in summer has a little ability to improve an arid situation.
Employing a data set of a precipitation amount 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 it plays a fundamental role in agricultural productivity. Plants and insects develop in accordance with temperature. The warmer weather, the faster they grow and reproduce, and otherwise, the colder, the slower the processes go.

All species have a biological minimum of a temperature level, and the development does not take place at all below this level. When temperature of 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 for a definite species of plants and insects.

Accumulated temperature (AT) represents an integrated excess or lack of temperature regarding a fixed starting point. This index is calculated as a sum of average daily temperature of air and soil, which exceeds a certain threshold of zero, 5, 10 degrees or a biological minimum of a temperature level.

Basically speaking, this is a way to include temperature and time into one dimension for quantitative evaluation of growth speed 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 the accumulated temperature data. API will be based on historical data and will be focused primarily on users from the agricultural sector.  

We are happy to announce that one of our products - API for UV-index has got significant improvement.    
- Now besides current and historical data, you can also get UVI forecasts for periods of 8 days.    
- Syntax has got considerably easier,  it has become clearer and more unified like other APIs version 2.5.  
- There is a new feature to request data on any geographic coordinates without limits on accuracy.
- Accuracy of UVI modeled data has been increased twice (the interpolation grid step decreased from 0.5 to 0.25 degrees).      
- Soon the support of search by city name, city id and zip-code will be available. 

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

Please pay attention that during 2 weeks UV-index data will be in open access.  Further, access to this data will be available only for paid plans starting from Developer. For more information on our plans please visit  http://openweathermap.org/price

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