{"id":795,"date":"2013-06-03T08:11:05","date_gmt":"2013-06-03T13:11:05","guid":{"rendered":"http:\/\/pages.charlotte.edu\/mesas\/?p=795"},"modified":"2013-06-02T20:31:22","modified_gmt":"2013-06-03T01:31:22","slug":"co2-trends-from-around-the-world","status":"publish","type":"post","link":"https:\/\/pages.charlotte.edu\/brian-magi\/2013\/06\/03\/co2-trends-from-around-the-world\/","title":{"rendered":"CO2 trends from around the world"},"content":{"rendered":"

Time series are profilic in climate science. This is a dataset that shows the how a measurement changes over some period of time. The best known in our world is the global warming time series displayed as the globally-averaged surface temperature trend, which is compiled from thermometer measurements. A few research groups worldwide maintain this analysis (NASA GISS<\/a>, UK Met Office<\/a>, NOAA NCDC<\/a>). Since CO2 is in the news, and since there is variability from one measurement location to another, it is useful to see how the best-known station in Mauna Loa, Hawaii<\/a> (source of the data<\/a> shown in the Keeling curve graph<\/a>). Once you navigate the shifting axes (y-axis on the right and left, and the time series begin at different points in the past) and digest the information visualized here, the graph below<\/a> is very useful in quickly understanding variability in CO2 concentration from the northernmost latitudes to the southernmost, noting the latitude is listed under the three-letter station identifier but that the graph is arranged north to south.\"co2-globaltrends\"There is clearly a bias toward higher CO2 in the northern hemisphere compared to the southern hemisphere – CO2 is about 10-12 ppm higher near the north pole. This piece of information – this data – reflects the higher abundance of sources<\/em> of CO2 in the northern hemisphere and the relatively slow transport times required for air to move across the equator<\/a> (like a slow drip compared to the winds we feel every day in the USA). The graph also effectively conveys another dimension of information: Regardless of the specific location of CO2 measurement, the long-term trend is essentially the same worldwide, indicating that CO2 continues to accumulate in the atmosphere worldwide<\/a> at about the same pace. The trend could relatively easily be quantified<\/a>, but sometimes qualitative analysis is enough. From the webpage where I found the figure<\/a>, the station identifiers are PTB = Point Barrow, LJO = La Jolla, MLO = Mauna Loa Observatory, CHR = Christmas Island, SAM = Samoa, and SPO = South Pole. You can also find some commonality in the stations at NOAA’s website<\/a>. All in all, a great data visualization that can be done entirely in black-and-white! <\/p>\n","protected":false},"excerpt":{"rendered":"

Time series are profilic in climate science. This is a dataset that shows the how a measurement changes over some period of time. The best known in our world is the global warming time series displayed as the globally-averaged surface temperature trend, which is compiled from thermometer measurements. A few research groups worldwide maintain this […]<\/p>\n","protected":false},"author":490,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"ngg_post_thumbnail":0,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[35],"tags":[69,48,15,73,77,24],"class_list":["post-795","post","type-post","status-publish","format-standard","hentry","category-earth-system-observer","tag-co2","tag-data-visualization","tag-global-warming","tag-noaa","tag-scripps","tag-spatiotemporal-analysis"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p2kjqv-cP","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/posts\/795","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/users\/490"}],"replies":[{"embeddable":true,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/comments?post=795"}],"version-history":[{"count":10,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/posts\/795\/revisions"}],"predecessor-version":[{"id":806,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/posts\/795\/revisions\/806"}],"wp:attachment":[{"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/media?parent=795"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/categories?post=795"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pages.charlotte.edu\/brian-magi\/wp-json\/wp\/v2\/tags?post=795"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}