Accessing In-Time Weather via API

Sample Code

Jumpstart your coding with these snippets of code.

SNI Compliance in Clients Calling API

Server Name Indication (SNI) Support Requirements

Calling API with TLS 1.2

Guidance on updating code for TLS 1.2

Browser Based Applications

How to make API calls from a browser-based application

Postman Collections

Using postman to explore our APIs.

Swagger Filers [GitHub]

Swagger Files


Your application can do much more than echo data from our APIs. These tutorials should help explain the background behind our APIs as well as the agronomic science they open up. The more context you understand, the better your app can be.

Introduction to RESTful APIs

aWhere’s API platform is built as REST-based web services. Any application or programming language that connects to and interact with the wider Internet can easily integrate our data. There are four essential parts to implementing RESTful APIs using HTTP—URIs, verbs, headers and status codes, and payloads.

Introduction to Growing Degree-Days (GDDs)

In agronomy the standard metric for heat measurement is the growing degree-day, or GDD (it’s also called a growing degree unit, GDU, but GDD is the more common term). While many other factors influence plant development, the GDD is a simple starting point that is used by most farmers for tracking their crop growth.

Introduction to Potential Evapotranspiration (PET)

Evapotranspiration is a metric that gauges how quickly water leaves the earth, either through evaporation or through a plant’s use of water (some of which is ultimately lost as water vapor). Water that leaves the earth needs to be replenished, either by rain or by irrigation, in order for plants to have sufficient supply to grow. Potential Evapotranspiration (PET) is the calculation, based on weather, of how much water is likely to evapotranspirate over a certain amount of time.

Distributing Weather and Agronomic Information Using ICT

This is a quick guide on the steps to define, build, and deploy a weather and agronomic information system for ICT.

Geospatial Resources (Maps4ER)

Getting Started

aWhere’s geospatial data seamlessly integrates with other GIS data to gain daily insights on your farms, industry or country.

QGIS Tutorial

This tutorial aims to get you started with aWhere data visualization and basis analysis in QGIS 3, free and open-source geographic information system software that enables viewing, editing, and analysis of geospatial data.

Geospatial Files

aWhere’s geospatial files allow users to visualize and analyze weather for the past 30 and 15-day forecast to deliver Economic Resilience (ER). Follow these steps to get started with a free trial today!

Weather Insights

Leveraging Open-Source Tools to Visualize aWhere’s Weather Data

This tutorial series will review how to leverage aWhere’s daily-updated, high resolution weather data and open source software such as R and QGIS. The outputs generated from both R and QGIS can enhance reports, inform decisions, and support your analysis.

▶ Step 1 : Organizing your File Structure

Why is file structure important? The short answer is that it enables you to find different input and output files to efficiently generate data products, charts and maps to generate insights and produce reports to achieve your objectives. The structure proposed here has evolved over the years based on practical experience that we want to pass on to you to position you for success in the use of R and QGIS.

▶ Step 2 : Accessing Resources on aWhere’s adaptER Platform

aWhere’s adaptER Platform offers both static and interactive maps to monitor world weather trends. Of interest for this training tutorial we will focus on the data download section of this platform which will allow us to utilize this data in QGIS.

▶ Step 3 : Getting your aWhere Key & Secret

In order to access aWhere’s historical and forecast data, you need to register for our API (application programming interface) and obtain your key and secret. This tutorial will review how to access your credentials to start pulling data from the API.

▶ Step 4 : Accessing aWhere’s R Scripts

This tutorial will review how to access aWhere’s R scripts through the adaptER Platform as well as GitHub and explain best practices of version control. If you have never used R before, not to worry – we will guide you through the steps to start generating powerful weather visuals!

▶ Step 5 : Using QGIS to make a map of aWhere’s GIS-ready Weather Files

This tutorial aims to get you started with aWhere data visualization and basic analysis in QGIS (now version 3.12), free and open-source geographic information system software that enables viewing, editing, and analysis of geospatial data.

▶ Step 6 : Generating a locations file in QGIS to use in R

This tutorial will show you how to collect a set of coordinates locations (latitude/longitude) to dig deeper into weather anomalies in your area of interest

▶ Step 7 : Getting Started with aWhere’s R Scripts

This tutorial aims to get you started leveraging R and RStudio to dig deeper into the historical and/or forecast weather trends for the locations you identified in the previous tutorial Generating Locations File in QGIS.

▶ Step 8 : Generating charts with R and where to find them

This tutorial aims to get you started with the main scripts that produce valuable data files (csv), graphs, and maps.

▶ Step 9 : Creating a map layout and adding shapefiles to your map

This tutorial aims to get you started with making a professional map that includes a legend and other cartographic elements in one layout. You can add these maps to your reports, bulletins, and use them to help inform decisions based on weather patterns viewed in the maps.

▶ Step 10 : Using aWhere’s outputs in a case study, report, bulletin

The final tutorial which will show you how to combine the charts, maps, figures, and data you have extracted over the course of the training to make meaningful reports, case studies and more to build resilience to climate change