Global Seismic Hazard Map

Global Earthquake Model Global Seismic Hazard Map
The Global Seismic Hazard Map depicts the geographic distribution
of the Peak Ground Acceleration (PGA) with a 10% probability of being exceeded in 50 years, computed for reference rock conditions (shear wave velocity, VS30, of 760-800 m/s). The map was created by collating maps computed using national and regional probabilistic seismic hazard models developed by various institutions and projects, and by Global Earthquake Model Foundation scientists. The OpenQuake engine, an open-source seismic hazard, and risk calculation software developed principally by the Global Earthquake Model Foundation were used to calculate the hazard values. A smoothing methodology was applied to homogenize hazard values along the model borders. The map is based on a database of hazard models described using the OpenQuake engine data format (NRML); those models originally implemented in other software formats were converted into NRML. While translating these models, various checks were performed to test the compatibility between the original results and the new results computed using the OpenQuake engine. Overall the differences between the original and translated model results are small, notwithstanding some diversity in modeling methodologies implemented in different hazard modeling software. The hashed areas in the map (e.g. Greenland) are currently not covered by a hazard model. The map and the underlying database of models are a dynamic framework, capable to incorporate newly released open models. Due to possible model limitations, regions portrayed with low hazard may still experience potentially damaging earthquakes.

Via globalquakemodel.org

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Find cities with similar climate

This map has been created using The Global environmental stratification. The Global environmental stratification (GEnS), based on statistical clustering of bioclimate data (WorldClim). GEnS, consists of 125 strata, which have been aggregated into 18 global environmental zones (labeled A to R) based on the dendrogram. Interactive map >> Via www.vividmaps.com Related posts: - Find cities with similar climate 2050 - How global warming will impact 6000+ cities around the world?

The Appalachian Mountains, the Scottish Highlands, and the Atlas Mounts in Africa were the same mountain range

The Central Pangean Mountains was a prominent mountain ridge in the central part of the supercontinent Pangaea that extends across the continent from northeast to southwest through the Carboniferous , Permian Triassic periods. The mountains were formed due to a collision within the supercontinents Gondwana and Laurussia during the creation of Pangaea. It was comparable to the present Himalayas at its highest peak during the start of the Permian period. It isn’t easy to assume now that once upon a time that the Scottish Highlands, The Appalachian Mountains, the Ouachita Mountain Range, and the Atlas Mountains in northwestern Africa are the same mountains , once connected as the Central Pangean Mountains.

Human Emotions Visualized

Despite significant diversity in the culture around the globe, humanity's DNA is 99.9 percent alike. There are some characteristics more primary and typical to the human experience than our emotions. Of course, the large spectrum of emotions we can feel can be challenging to verbalize. That's where this splendid visualization by the Junto Institute comes in. This visualization is the newest in an ongoing attempt to categorize the full range of emotions logically. Our knowledge has come a long route since William James suggested 4 primary emotions: fear, grief, love, and rage. These kernel emotions yet form much of the basis for current frameworks. The Junto Institute's visualization above classifies 6 basic emotions: fear, anger, sadness, surprise, joy, love More nuanced descriptions begin from these 6 primary emotions, such as jealousy as a subset of anger and awe-struck as a subset of surprise. As a result, there are 102 second-and third-order emotions placed on this emo

Ecoclimax

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