{"id":263,"date":"2021-02-07T09:26:33","date_gmt":"2021-02-07T09:26:33","guid":{"rendered":"http:\/\/www.martin-rdz.de\/?p=263"},"modified":"2021-12-23T10:36:02","modified_gmt":"2021-12-23T10:36:02","slug":"blue-planet","status":"publish","type":"post","link":"http:\/\/www.martin-rdz.de\/index.php\/2021\/02\/07\/blue-planet\/","title":{"rendered":"Blue Planet"},"content":{"rendered":"<p>How much of the Earth&#8217;s surface is covered by water? &#8211; 2\/3 elementary school knowledge. But how to confirm? And what fraction of the southern hemisphere mid-latitudes is covered by ocean?<\/p>\n<p>We need some data first. For a quick shot, the MODIS land cover type classification should be sufficient. <a href=\"https:\/\/lpdaac.usgs.gov\/products\/mcd12c1v006\/\">MCD12C1<\/a> provides global coverage at 0.05\u00b0 in the HDF4 format. It is a resampled and\u00a0 stitched together version of the 500m <a href=\"https:\/\/lpdaac.usgs.gov\/products\/mcd12q1v006\/\">MCD12Q1<\/a> version. The <a href=\"https:\/\/lpdaac.usgs.gov\/documents\/101\/MCD12_User_Guide_V6.pdf\">user guide<\/a> provides a nice overview.<\/p>\n<p>Now we need to do some calculations. The <a href=\"https:\/\/gist.github.com\/martin-rdz\/1ac6a43f0cd63ece9b4ad94d5ef8adef\">python jupyter notebook is on github<\/a>. The recipe is rather simple: Load the HDF4 dataset, select the IGBP<sup>[1]<\/sup> classification, quick plot for visualization, get the projection and the pixel sizes right and finally do some conditional sums.<\/p>\n<p>The projections and the pixel sizes are a crucial point. The dataset is in the <a href=\"https:\/\/modis-land.gsfc.nasa.gov\/MODLAND_grid.html\">MODIS climate modeling grid<\/a>, which is a geographic lat-lon projection. The pixel area gets smaller towards the poles, which we have to keep in mind, when <a href=\"https:\/\/en.wikipedia.org\/wiki\/Geographic_coordinate_system#Length_of_a_degree\">calculating the size of the per pixel<\/a>.<\/p>\n<p>Looking at the final numbers, the fraction of water is 71.6%, which is sufficiently close to available estimates. Some discrepancy is expected, as we do not include ice shelfs, sea ice, tides, etc and the underlying resolution is &#8216;only&#8217; 5km. Barren surfaces cover around 4.0% of the Earth (13.9% of the land) and ice sheets, including permanent snow cover 2.9% (10.2% of the land).<\/p>\n<p>When splitting up the hemispheres, in the Northern Hemisphere water covers 61.4%, barren 7.5% and ice less than 1%. Of all the land, barren surfaces cover 19.4%. In the Southern Hemisphere, water makes up 81.8% of the surfaces, with barren less than 0.5% and ice 4.8%.<\/p>\n<p>Finally the mid-latitudes. As a rather crude definition, the latitudes between 30\u00b0 and 70\u00b0 are used. In the northern mid-latitudes water covers 48.0% (5.7% barren and 0.7% ice). Barren surfaces make up 11.0% of the land. The southern mid-latitudes are overwhelmingly covered with water (93.9%, barren &lt;0.2%, ice 1.4%).<\/p>\n<p>[1] I<span class=\"\">nternational Geosphere-Biosphere Programme: <a href=\"http:\/\/www.igbp.net\/\">http:\/\/www.igbp.net\/<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How much of the Earth&#8217;s surface is covered by water? &#8211; 2\/3 elementary school knowledge. But how to confirm? And what fraction of the southern hemisphere mid-latitudes is covered by ocean? We need some data first. For a quick shot, the MODIS land cover type classification should be sufficient. MCD12C1 provides global coverage at 0.05\u00b0 &hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6,7,5],"tags":[],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/posts\/263"}],"collection":[{"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/comments?post=263"}],"version-history":[{"count":4,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/posts\/263\/revisions"}],"predecessor-version":[{"id":267,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/posts\/263\/revisions\/267"}],"wp:attachment":[{"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/media?parent=263"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/categories?post=263"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.martin-rdz.de\/index.php\/wp-json\/wp\/v2\/tags?post=263"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}