{"id":166,"date":"2017-04-11T10:50:47","date_gmt":"2017-04-11T10:50:47","guid":{"rendered":"http:\/\/blogs.reading.ac.uk\/dare\/?p=166"},"modified":"2018-10-08T12:25:46","modified_gmt":"2018-10-08T11:25:46","slug":"7th-japanese-data-assimilation-workshop","status":"publish","type":"post","link":"https:\/\/research.reading.ac.uk\/dare\/2017\/04\/11\/7th-japanese-data-assimilation-workshop\/","title":{"rendered":"7th Japanese Data Assimilation Workshop"},"content":{"rendered":"

By<\/em> J<\/em>oanne A. Waller <\/em><\/p>\n

For decades data assimilation (DA) has played a crucial role in numerical weather prediction (NWP) where it is used to provide initial conditions for weather forecasts. These \u2018initial conditions\u2019 describe the current atmospheric state and are estimated using data assimilation by blending previous forecasts with atmospheric observations, weighted by their respected uncertainties. However data assimilation is not only applicable to NWP and in recent years it has been applied widely to different applications where numerical simulations and observations are available.<\/p>\n

At the end of February 2017 over 100 scientists from around the globe arrived at the Japanese RIKEN Advanced Institute for Computational Science (AICS)\u00a0 for the 7th Japanese Data Assimilation Workshop<\/a>. The aim of the symposium was to bring together scientist from from numerous different disciplines, such as neuroscience, cardiology, molecular dynamics, cosmology, nanoscale materials science, terrestrial magnetism, paleoclimate, oceanography, atmospheric chemistry and of course NWP, to discuss the data assimilation issues shared\u00a0 across these broad applications.<\/p>\n

Presentations and posters covered a wide variety of topics including: how data assimilation combined with advanced intelligence can help improve numerical models; how high performance computing can be used to deal with the new era of \u2018Big Data\u2019; how non-Gaussianity and non-linearity can be handled in data assimilation; ideas on how assimilate data into multi component models (i.e. systems that connect multiple models such as atmospheric, land and ocean models) and many more.<\/p>\n

The conference provided a perfect platform for many cross-disciplinary discussions and this highlighted that much can be learnt in general about data assimilation by considering the issues that arise across different scientific areas.<\/p>\n

<\/p>\n

(Photo from http:\/\/www.data-assimilation.riken.jp\/risda2017\/)<\/p>\n","protected":false},"excerpt":{"rendered":"

By Joanne A. Waller For decades data assimilation (DA) has played a crucial role in numerical weather prediction (NWP) where it is used to provide initial conditions for weather forecasts….Read More ><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[3,4],"tags":[12],"class_list":["post-166","post","type-post","status-publish","format-standard","hentry","category-conferences","category-data-assimilation","tag-big-data"],"acf":[],"yoast_head":"\n7th Japanese Data Assimilation Workshop - DARE<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/research.reading.ac.uk\/dare\/2017\/04\/11\/7th-japanese-data-assimilation-workshop\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"7th Japanese Data Assimilation Workshop - DARE\" \/>\n<meta property=\"og:description\" content=\"By Joanne A. 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