{"id":5983,"date":"2020-12-31T09:15:27","date_gmt":"2020-12-31T15:15:27","guid":{"rendered":"https:\/\/steve.cooleysekula.net\/blog\/2020\/12\/31\/muon-weather-and-seasons\/"},"modified":"2020-12-31T20:32:58","modified_gmt":"2021-01-01T02:32:58","slug":"muon-weather-and-seasons","status":"publish","type":"post","link":"https:\/\/steve.cooleysekula.net\/blog\/2020\/12\/31\/muon-weather-and-seasons\/","title":{"rendered":"Muon Weather and Seasons"},"content":{"rendered":"\n<p>Over the winter break, I have picked up my little muon detector data side project that started in the spring term of 2020. A few days ago, I remarked on how I wanted to take account of \u201cweather\u201d in the data &#8211; variations around a daily expectation given seasonal conditions &#8211; and \u201cseasons\u201d &#8211; long-term trends in the data. <\/p>\n\n\n\n<p>Based on almost 290 days of data since I began this project, it was clear that the counts vary with time with short-period and long-period trends. Let us define a muon \u201ctimeblock\u201d as a quarter-hour (15 minute) duration of data-taking. In a single timeblock, the detector typically reports the passage of about 1000 muons. What 290 days of data has taught me is what many previous experiments have also seen: there are overall fewer muons per timeblock in colder months and more in warmer months. So there is something of an annual overall trend, sinusoidal in shape, as well as shorter-term variations (hourly, daily, over multiple weeks, etc.). <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096-1024x683.png\" alt=\"\" class=\"wp-image-5981\" srcset=\"https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096-1024x683.png 1024w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096-300x200.png 300w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096-768x512.png 768w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096-640x427.png 640w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1096.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>Seasonal effects in muon data. The rate in a given timeblock has the average timeblock count (computer over the past 365 days) subtracted from it. \u201cWinter-like\u201d conditions occur when the rate is more than 1\/2 standard deviation below 0. A standard deviation is determined from the the counts over the past 365 days. \u201cTransitional\u201d conditions (spring- or fall-like) occur within 1\/2 standard deviation of the mean; \u201csummer-like\u201d occur more than 1\/2 standard deviation above the mean. <\/figcaption><\/figure>\n\n\n\n<p>I have now captured the seasonal effect using s sine function model. This is fitted to all previous days of data, excluding the current one, to find the best model parameters that describe the past. Today\u2019s rate is then extrapolated from the function, including the effect of model parameter statistical uncertainty from the fitting process. This allows me to identify \u201cweather\u201d conditions &#8211; deviations from the daily expectations. <\/p>\n\n\n\n<p>It is currently \u201cwinter-like\u201d now. That means we expect, on average, the muon rate to be below the yearly average. Yesterday, we saw additionally \u201ccolder\u201d muons weather, with quite a lull in muon counts given the expected rate in each timeblock.  Today, things appear to be \u201cheating\u201d back to the expectation, and we will see where the day takes us. <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095-1024x683.png\" alt=\"\" class=\"wp-image-5982\" srcset=\"https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095-1024x683.png 1024w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095-300x200.png 300w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095-768x512.png 768w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095-640x427.png 640w, https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095.png 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>An example of \u201cweather\u201d from the past 24 hours. The muon count in each timeblock has the sine function fit expectation for that day subtracted from it. We had a slightly colder snap yesterday than expected from the seasonal rate, but today it seems to have \u201cwarmed\u201d back to normal &#8230; meaning muon counts are more consistent with the seasonal expectation today. <\/figcaption><\/figure>\n\n\n\n<p>You can find the current muon weather at SMU on my computational lab site, SA-SO (the SMU All-Scale Observatory, my name for my virtual laboratory space at SMU): <a href=\"https:\/\/blog.smu.edu\/saso\/projects\/muon-observatory\/#Muon_Weather_Conditions\">https:\/\/blog.smu.edu\/saso\/projects\/muon-observatory\/#Muon_Weather_Conditions<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Over the winter break, I have picked up my little muon detector data side project that started in the spring term of 2020. A few days ago, I remarked on how I wanted to take account of \u201cweather\u201d in the data &#8211; variations around a daily expectation given seasonal conditions &#8211; and \u201cseasons\u201d &#8211; long-term [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":5982,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[21,9,6],"tags":[],"class_list":{"0":"post-5983","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-faculty-life","8":"category-physics","9":"category-science","10":"czr-hentry"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/steve.cooleysekula.net\/blog\/wp-content\/uploads\/2020\/12\/img_1095.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/posts\/5983","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/comments?post=5983"}],"version-history":[{"count":1,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/posts\/5983\/revisions"}],"predecessor-version":[{"id":5984,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/posts\/5983\/revisions\/5984"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/media\/5982"}],"wp:attachment":[{"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/media?parent=5983"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/categories?post=5983"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/steve.cooleysekula.net\/blog\/wp-json\/wp\/v2\/tags?post=5983"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}