Weather patterns are dynamic and complex phenomena that affect our lives and environment. How can we use Geographic Information Systems (GIS) to visualize and communicate weather data on a map? In this article, you will learn about some of the most effective ways to show weather patterns on a map using GIS tools and techniques.
The first step to show weather patterns on a map is to find and access reliable and relevant weather data sources. Weather data can come from various sources, such as satellite imagery, radar, ground stations, models, and forecasts. Depending on your needs and objectives, you may want to use different types of weather data, such as temperature, precipitation, wind, pressure, humidity, cloud cover, and more. You can find many weather data sources online, such as the National Weather Service, NOAA, NASA, and other agencies and organizations. Some of these sources provide data in GIS-ready formats, such as shapefiles, raster files, or web services, while others may require some preprocessing or conversion.
One of the most difficult aspects of environmental and climate data is obtaining reliable field data. In the case of precipitation, most often rain gauges are installed near airports and in easily accessible locations. However, rainfall data upstream of watersheds, particularly in the case of tropical islands which are often steep and very humid, is essential for anticipating episodes of flash floods. In these cases, the rain gauge is difficult to access, requiring off-road vehicles and driving time. But the efforts made to be able to have this data are priceless, because this specific data makes it possible to validate and best calibrate forecast models based on radar data for example.
The second step to show weather patterns on a map is to choose and use appropriate weather data formats. Weather data formats can be classified into two main categories: vector and raster. Vector data consists of points, lines, and polygons that represent discrete features or locations, such as weather stations, fronts, or boundaries. Raster data consists of pixels or cells that represent continuous values or surfaces, such as temperature, precipitation, or elevation. Both vector and raster data have advantages and disadvantages for showing weather patterns on a map. Vector data can show precise locations and attributes, but may not capture the spatial variation and distribution of weather phenomena. Raster data can show the spatial variation and distribution of weather phenomena, but may not provide detailed information or resolution.
The third step to show weather patterns on a map is to apply and adjust suitable weather data visualization techniques. Weather data visualization techniques can be divided into two main types: static and dynamic. Static visualization techniques use symbols, colors, labels, and legends to represent weather data on a map. Static visualization techniques can be simple or complex, depending on the level of detail and information you want to convey. For example, you can use point symbols to show the location and temperature of weather stations, or you can use contour lines or isolines to show the variation and gradient of temperature across an area. Dynamic visualization techniques use animation, interactivity, and time series to represent weather data on a map. Dynamic visualization techniques can be more engaging and informative, but also more challenging and resource-intensive. For example, you can use animation to show the movement and change of weather patterns over time, or you can use interactivity to allow users to explore and query weather data on a map.
The fourth step to show weather patterns on a map is to perform and present relevant weather data analysis. Weather data analysis can help you understand and explain the causes, effects, and trends of weather patterns on a map. Weather data analysis can involve various methods and techniques, such as spatial statistics, spatial modeling, spatial interpolation, spatial correlation, and spatial regression. Weather data analysis can help you answer questions such as: How does weather vary across space and time? What are the factors that influence weather patterns? How does weather affect other variables or phenomena? How can we predict or forecast weather patterns? You can use GIS tools and functions to conduct and display weather data analysis on a map, such as charts, graphs, tables, indicators, and reports.
The fifth step to show weather patterns on a map is to communicate and share your weather data and findings with your audience. Weather data communication can have different purposes and goals, such as informing, educating, persuading, or entertaining. Weather data communication can also have different formats and platforms, such as reports, presentations, websites, or social media. Weather data communication can require different skills and strategies, such as storytelling, design, accessibility, and ethics. Weather data communication can help you achieve various outcomes and impacts, such as awareness, understanding, action, or change. You can use GIS tools and features to create and distribute your weather data communication products, such as maps, dashboards, stories, or apps.
The sixth and final step to show weather patterns on a map is to acknowledge and address the potential challenges and limitations of weather data. Weather data can pose various challenges and limitations for showing weather patterns on a map, such as accuracy, reliability, availability, compatibility, scalability, and security. Weather data can also raise various issues and concerns, such as privacy, ethics, bias, and responsibility. Weather data can also generate various opportunities and innovations, such as new sources, methods, applications, and solutions. You can use GIS tools and practices to overcome and improve your weather data challenges and limitations, such as quality control, data integration, data transformation, data visualization, and data dissemination.