Analyzing Ice Water Content in GFS Files: Unveiling Insights into Cloud Microphysics
Weather & ForecastsDecoding Ice in the Sky: What GFS Files Tell Us About Cloud Secrets Ever looked up at a cloud and wondered what it’s really made of? Turns out, a big part of the story is ice – specifically, how much ice is floating around up there. We call that “ice water content,” or IWC for
Converting Surface Roughness from mm to Strickler Coefficient: A Model-Based Approach for Earthscience Applications
Modeling & PredictionDecoding the Landscape: Turning Roughness into River Flow with the Strickler Coefficient Ever wondered how scientists predict floods or figure out where the best fish habitats are in a river? A big part of that puzzle is understanding how water flows across the land, and that’s where surface roughness comes in. Imagine water rushing over
Has a scientific consensus been reached concerning the formation of the Grand Canyon?
Geology & LandformThe Grand Canyon: Cracking the Code of Its Creation The Grand Canyon. Just the name conjures up images of immense scale, doesn’t it? It’s a colossal gash in the Arizona landscape, a place that screams of geological power and the relentless march of time. For over a century, scientists have been trying to unravel its
Converting SRTM to XYZ, ORD, and GRD: Essential Techniques for Earth Science and GIS Applications
Hiking & ActivitiesDecoding Earth: Turning SRTM Data into XYZ, ORD, and GRD – A Practical Guide Ever wondered how we get those amazing 3D maps of the Earth? A big part of it comes from something called the Shuttle Radar Topography Mission, or SRTM for short. This mission gave us a near-global digital elevation model (DEM), which
Visualizing Paleoclimate Data: A Guide to Plotting Multiple Timeseries with MATLAB’s Common X Axis and Stacked Y Axes
Climate & Climate ZonesVisualizing Paleoclimate Data: Making Sense of Earth’s Climate History with MATLAB Ever wonder how scientists piece together what Earth’s climate was like thousands, even millions, of years ago? It’s a fascinating puzzle, and a big part of solving it comes down to analyzing and visualizing time-series data. Think ice core records, layers of sediment –
Locating the Closest Non-NaN Value in a 2D Xarray Dataset: A Python Guide for Earth Science Applications
Software & ProgrammingFinding the Needle in the Haystack: Locating the Closest Valid Data in Your Earth Science Datasets (and Why You Should Care) Okay, let’s face it: Earth science data isn’t always perfect. We’re talking missing values galore – those pesky NaNs (Not a Number) that pop up in our datasets like uninvited guests. Maybe a sensor