Articles in “API”

Ocean CO2 Data Since 1970

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Oceans absorb approximately half of man-made CO2 emissions. The warming of the ocean surface and changes in wind patterns can limit the transfer of CO2 to deeper levels and thus limit oceans ability to absorb greenhouse gases. Shifts in the biological pump and ecosystem functioning are also likely to appear.

This week we’ve added Surface Ocean CO2 Variability and Vulnerability (Socat V4) dataset to Planet OS Datahub.

With historical data since 1970, the Socat V4 dataset is the common format of all publicly available fugacity of CO2 data for the oceans surface. It has become the foundation for the marine carbon community upon which they build the future.

Curious to find out more? Explore all datasets on Planet OS Datahub.

35 Years of Sea Surface Temperature

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This week we’ve added several decades of historical NOAA Daily OISST data to our Datahub. The dataset is an analysis constructed by combining observations from different platforms (satellites, ships, buoys) on a regular global grid, with values from 1981 until now.

In addition to standard sea surface temperature, the Daily Optimum Interpolation Sea Surface Temperature dataset also includes SST anomalies, which means the daily OISST minus a 30-year climatological mean.

The Daily OISST data are great for investigating upwellings and downwellings, and have been used to track signs of El Niño and La Niña. In fact, forecasters now think there’s a 70% chance that La Niña conditions will develop this fall.

Looking for Earth data? Explore the Planet OS Datahub.

Baltic Sea Real Time Observations Now Available

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This week we’ve added Baltic Sea Real Time Observations to Planet OS Datahub.

The Baltic Sea recently experienced a significant sea level drop which can be easily viewed with this timeseries dataset. Due to three weeks long eastern winds and high air pressure, over 200 km3 of water was blown from the Baltic Sea into the ocean through the Scandinavian straits.

Baltic Sea observations data are collected from 150 stations and includes sea surface temperature, sea surface height and wave properties. The dataset provides observations within 24 to 48 hours of acquisition, with quality controlled according to standardized procedures that have been defined in collaboration with BOOS (Baltic Operational Oceanographic System).

Are you working with Earth science data? Planet OS Datahub streamlines the data integration process and reduces operational overhead. Stop wrestling with undocumented interfaces, outdated formats, and broken integration scripts. With Datahub you can focus on what truly matters – delivering valuable data-driven insights and applications. See what other high-quality data we have made available.

Planet OS Data Challenge at ExpeditionHack NYC

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We’re thrilled to be part of the Expedition Hackathon NYC happening on November 12-13! This is your chance to map the future of sustainability with NGA, Mapbox, IBM Bluemix, Planet OS and others. The hackathon’s focus areas are Oceans, Forests, Conservation and Indigenous People.

To add some motivation to the hours of intense coding and hustling, we decided to put out tons of high-quality environmental data, data integration and computational infrastructure, and reward the best teams with some cool prizes.

All hackathon participants will get free, unlimited access to:

The prizes:

  • All teams that use our data tools will secure an unlimited free access to Planet OS data tools
  • The team with the best solution will get special swag and surprises from Planet OS
  • The general Grand Prize of the hackathon is $3000 and a round trip to DC from NGA to meet NGA Executives.

We have already validated a few business ideas that the teams could work on. Stay tuned for updates! All the updates will be shared on this page so it would be wise to bookmark it. Contact us at aljash@planetos.com for further questions.

#PlanetOS  #DataChallenge

Join Planet OS Data Challenge At Garage48

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We’re thrilled to be part of the Garage48 Open & Big Data Hackathon happening this weekend in Tartu, Estonia! To add some motivation to the 48h of intense coding and hustling, we decided to put out tons of high-quality environmental data, data integration and computational infrastructure, and reward the best teams with some cool prizes.

All hackathon participants will get free, unlimited access to:

The prizes:
- All teams that use our data tools will secure an unlimited free access to Planet OS data tools
– Three teams with the best solutions will get special swag and surprises from Planet OS
– The team that comes out with the best prototype that runs on Planet OS Datahub, will be rewarded with €1,000!

We have already validated a few business ideas that the teams could work on. Stay tuned for updates! All the updates will be shared on this page so it would be wise to bookmark it. Note that you will definitely stand out if your solution uses some elements of Machine Learning.

#PlanetOS  #DataChallenge

Carbon Dioxide Data Now Available On Datahub

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The carbon dioxide data, measured at the premier atmospheric research facility, Mauna Loa Observatory in Hawaii, is now available in Datahub:

The data, measured as the mole fraction in dry air, constitute the longest record of direct measurements of CO2 in the atmosphere dating back to May of 1974. As this dataset has a long, properly measured time series, it’s been widely used to show the connection between the level of Carbon Dioxide and global climate warming. Also, the unique geographic location of Mauna Loa Observatory – far from big industries and air pollution – makes it a reliable source.

The data are reported as a dry mole fraction defined as the number of molecules of carbon dioxide divided by the number of molecules of dry air multiplied by one million (ppm).

In addition to the carbon dioxide data, there are thousands of variables of other high-quality Earth Science data available in Datahub. Now that different kind of weather, climate, and oceanic data is made easy to find and work with, it’s time to build your own application. Let me know at annika@planetos.com if you want to discuss your idea.

New NAM Weather Forecast Data Now Available

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This week we’ve added an additional NAM weather forecast to the Planet OS Datahub, which now provides API access to seven North American Mesoscale Forecast System products:

NAM dataset provides a 60-hour forecast of pressure-level fields at 1-hourly and 3-hourly time steps and covers the contiguous United States at a 5 km resolution.

Researchers use NAM as a driver for complex air pollution simulations, but it is also used by public and private meteorologists to guide near-term weather forecasts within the United States. In a hierarchy of weather forecast models, it falls between the global medium range forecast GFS and the rapid refresh model HRRR.

Visit the Planet OS Datahub to access this dataset and over 2,100 variables from the world’s leading Earth Science data publishers. Interested in discussing different datasets and developer tools with researchers, developers and data scientists from around the world? Join our Slack community:

Planet OS Community on Slack

High-Resolution Rapid Refresh (HRRR) and Precipitation Data

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This week we added three new datasets to Datahub, including NOAA’s High-Resolution Rapid Refresh (HRRR) forecast for the contiguous United States.

High-Resolution Rapid Refresh (HRRR)
HRRR is a short range weather forecast that gives accurate estimates of the weather over the next few hours. Forecasted parameters are provided at a 3 kilometer spatial resolution, making it valuable for forecasters who can now investigate and monitor storm fronts with much greater detail. Having higher resolution short term data is important for better localized weather forecasts, and could also help pilots and air traffic controllers detect pockets of turbulence with greater accuracy.

In addition to HRRR, we’ve also added two precipitation datasets:

Precipitation analysis is essential in agriculture and forestry for estimating crop and fire hazard. Quantitative precipitation forecast is simple product based on ensemble forecast and giving the most accurate precipitation outlook for the next several days.

And in case you missed it, last week David Berlind from ProgrammableWeb shared his experiences working with the Planet OS API in his post How Dynamic Personalization of API Documentation Improves the Developer Experience.

“What makes [the documentation] great is how it already includes my actual API key (which I obfuscated for obvious reasons) which makes the entire string cuttable and directly pastable into my API calls whether they’re run from my source code in a language like Javascript or Python, or from the cURL utility at my command prompt.”

Thanks for the kind words David!

Photo courtesy of NOAA.

Investigate NASA Climate Data Using Planet OS Climate Data Access Tool

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There used to be only two ways to work with climate models: run complex fluid dynamics code on a supercomputer or look at a picture or graph made by someone who did. NASA and Amazon have changed that by publishing the results of model runs from institutions around the world as part of their OpenNEX program. Anyone can now access these datasets for free, meaning that researchers, journalists, students, (quantitative) analysts, risk modelers, etc., can explore the conclusions of top climate change investigators.

Last week, our team at Planet OS announced the OpenNEX Data Access Tool that makes working with this data much easier. With an interactive web interface and transformation tools packaged using state-of-the-art container technology, doing hands-on work with climate model results is now convenient for all who are interested. The OpenNEX data tool is especially valuable for professionals from insurance, agriculture, energy, transportation and many other industries affected by climate.

Next Wednesday, September 21st, Dr. Sangram Ganguly and I will give a webinar where we demonstrate in very practical terms how to select and use this tool to access and use the results of the climate models.

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Air Quality Data: Ozone Concentration & Fine Particulate Matter

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We’ve just added two air quality datasets to Datahub. Ozone concentration and fine particulate matter are two of the five “criteria” pollutants regulated under the U.S. Clean Air Act. Now you can use the Planet OS API to get a 48-hour forecast for each.

While air quality in the United States has improved significantly since the 1970 Clean Air Act, poor air quality is still responsible for an estimated 80,000 premature deaths in the United States each year. In fact, a recent study reports that in 2013, 87% of the world’s population lived in areas exceeding the World Health Organization (WHO) Air Quality Guideline of 10 μg/m3 PM2.5 (annual average).

The National Air Quality Forecast System (AQFS) was developed in support of a Congressional mandate to implement an operational air quality forecast system that benefits public health. Through a partnership between the National Oceanic and Atmospheric Administration (NOAA) and Environmental Protection Agency (EPA), daily air quality forecast guidance is produced for a variety of pollutants and particulate matter.

Today we’ve added two of those Air Quality Forecast System products to Datahub, which can now be accessed via the Planet OS API:

Each of these datasets is updated twice daily and provides a 48-hour forecast at a 1-hour resolution with a spatial extent covering the contiguous United States.

Photo via Michael Davis-Burchat.