Weather-based automation examples

This isn’t the National Weather Service, it’s Walmart. Weather data isn’t just for your local forecast anymore. It’s becoming one of the most powerful and underutilized signals in modern business. Companies like Walmart, Amazon, and UPS are taking this to a new degree by making real time decisions based on the weather. Walmart’s in-house meteorology team (seen below) uses storm patterns to predict what customers will need before they know they need it. Warm front? Stock up on ACs and towels. Blizzard incoming? Time to push shovels and hot chocolate. What is stranger as pointed out by Morning Brew is that when there is no wind, berry sales skyrocket so they run targeted ads in calm zip codes. Sometimes sales as much as triple. This is what happens when you have a systems level integration of weather data into your operations. But most companies still can’t do this. Because integrating weather and climate data into analytics workflows has been painfully hard: 📦 Data formats are often obscure, array based cubes or NetCDF files not easily queryable. 🌐 APIs are rate-limited, difficult to scale, and often require custom logic. 🧠 Domain expertise is needed just to parse and understand it—let alone act on it. Most teams still rely on humans to interpret forecasts manually, or bolt on weather data as a sidecar to their analytics pipeline. That’s changing. New tools and platforms are making it possible to: 🔎 Query gridded climate data like tabular data. ☁️ Store time-series and multidimensional arrays in open formats like Zarr and NetCDF in the cloud. ⛈️ Treat weather as just another dimension in your feature engineering stack not an exotic or nice-to-have external input. When weather becomes part of the system it unlocks a massive new layer of intelligence. And if Walmart is tripling sales on berries based on wind speed imagine what your business could do when climate becomes code. 🌎 I'm Matt and I talk about modern GIS, geospatial data engineering, and AI and geospatial is changing. 📬 Want more like this? Join 7k+ others learning from my newsletter → forrest.nyc

Local Weather Data x Critical Risk Management We talk a lot about environmental impacts on high-risk activities—like wind speed & direction impacting crane lifts, work at height, and heavy equipment operations—but how representative is the weather data we rely on? Most of the time, we use forecasted conditions from national meteorological services which are great for general awareness but often don’t reflect site-specific conditions. A forecast from a weather station 30km away doesn’t capture sudden wind gusts at a crane lift zone, temperature variations on-site, or microclimates created by terrain. Having local, real-time weather data at the actual worksite enables better risk management decisions. Instead of relying on broad forecasts, organisations can monitor live conditions at the precise location where critical work is happening. PLUS you get your own comprehensive data set for analytics... In the photos I'm holding a Davis EnviroMonitor Gateway LTE & Vantage Pro2 GroWeather Sensor Suite which is an example of a local weather monitoring system. This system provides real-time, hyper-local weather data directly from the worksite, enabling data-driven risk management decisions. It delivers real-time updates every 2.5 seconds; has wind speed, temperature, humidity, and rainfall monitoring plus solar radiation and evapotranspiration data which is also valuable for heat stress risk. This model has LTE connectivity (basically you can stick a SIM card in it) for remote monitoring and integration with cloud platforms. These systems aren't that expensive and offer new insights for local risk management that I've found can make a pretty big difference to your risk control strategy. Is anyone else implementing local weather systems for crane ops or other critical risk management? #safetytech #safetyinnovation #IoT

For businesses like basement waterproofing, where customer demand spikes during and after rain, automating your Google Ads campaigns based on local weather conditions can significantly optimize your ad spend. This blog post provides a step-by-step guide to creating a Google Ads script that starts and pauses your campaigns based on real-time weather data, ensuring your ads are most visible when potential customers are actively seeking your services.

Integrating weather data into SCADA for smarter stormwater management. One of the most underrated upgrades I’ve worked with is pulling live weather data directly into SCADA systems. It makes a huge difference—especially during storm events. We’re talking automated pump control, proactive overflow prevention, and better coordination with emergency response teams. I’m a big believer that real-time weather + automation = serious value for any municipality managing stormwater infrastructure. Have you explored this kind of integration in your systems yet? Let’s talk smart water management. #SCADA #Stormwater #Automation #SmartInfrastructure #WaterTech