Converting Surface Roughness from mm to Strickler Coefficient: A Model-Based Approach for Earthscience Applications
Modeling & Prediction1. Understanding Surface Roughness and Strickler Coefficient Surface roughness and Strickler coefficient are essential parameters in hydraulic engineering and hydrology, especially when analyzing flow characteristics in open channels and rivers. Surface roughness refers to irregularities or variations in the bed and banks of a channel that can affect the resistance to flow. The Strickler coefficient,
Has a scientific consensus been reached concerning the formation of the Grand Canyon?
Geology & LandformGetting Started The Grand Canyon, located in the southwestern United States, is one of the world’s most magnificent natural wonders. Spanning approximately 277 miles and reaching depths of over a mile, it features stunning geological formations that have captivated scientists, researchers, and visitors alike for centuries. The formation of the Grand Canyon is a topic
Converting SRTM to XYZ, ORD, and GRD: Essential Techniques for Earth Science and GIS Applications
Hiking & ActivitiesConverting .SRTM to XYZ, ORD, GRD: A Comprehensive Guide The Shuttle Radar Topography Mission (SRTM) dataset is a valuable source of accurate elevation data for the Geographic Information Systems (GIS) and Earth Science communities. However, SRTM data are typically provided as Digital Elevation Models (DEMs) in the .SRTM file format, which may not be directly
Visualizing Paleoclimate Data: A Guide to Plotting Multiple Timeseries with MATLAB’s Common X Axis and Stacked Y Axes
Climate & Climate ZonesGetting Started In the field of paleoclimate and earth science, the analysis and visualization of multiple time-series data is critical to understanding long-term climate patterns and changes. MATLAB, a popular programming language and scientific computing environment, provides powerful tools for plotting and analyzing such data. In this article, we will explore how to use MATLAB
Locating the Closest Non-NaN Value in a 2D Xarray Dataset: A Python Guide for Earth Science Applications
Software & ProgrammingHow to find the nearest non-NaN value in a 2D xarray dataset When working with large datasets in Python, especially in the geosciences, it is common to encounter missing or NaN (not a number) values. These missing values can pose challenges when performing computations or analyses on the dataset. One common task is to find
Unveiling the Optimal Forecast Hour for Earth Science Products: A Deep Dive into GFS Technology
Weather & ForecastsUnderstanding the Forecast Hour of an Earth Science Product: An Essential Component of GFS 1. What is the Forecast Hour of a Product? In the field of geosciences and meteorology, a product’s forecast hour refers to the specific period of time for which a particular weather forecast is valid. It represents the projected period of