{"id":1570,"date":"2019-03-08T19:50:32","date_gmt":"2019-03-08T19:50:32","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=1570"},"modified":"2020-03-08T23:24:07","modified_gmt":"2020-03-08T23:24:07","slug":"uk-weather-trends-8-winter-2019","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-8-winter-2019\/","title":{"rendered":"UK Weather Trends #8 &#8211; Winter 2019"},"content":{"rendered":"<p>The winter of 2019 was consistent with the step change in the winter climate that took place in the 1990s.<\/p>\n<p><!--more--><\/p>\n<p>Meteorologists define winter in the UK to be the period from December to February so winter is now over and we are officially in spring.<\/p>\n<p>I analyse the long term trends in the UK weather using a statistical tool known as <a href=\"https:\/\/en.wikipedia.org\/wiki\/Standard_score\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Standardisation<\/strong><\/a>.\u00a0 This means that the 3 key variables of Temperature, Sunshine and Rainfall are recalculated so that they all have the same units, which is number of standard deviations above or below the mean.\u00a0 Such variables are known as <strong>Z-Scores<\/strong>\u00a0which by definition will have a mean value of 0 and a standard deviation of 1.\u00a0 For more information on how I have done this, <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-2-summer-2017\/\" target=\"_blank\" rel=\"noopener noreferrer\">please read my post on trends in the UK summer of 2017.<\/a><\/p>\n<h4><span style=\"color: #008000\"><strong>Latest Z-Scores<\/strong><\/span><\/h4>\n<p>The Z-Scores for Temperature, Sunshine and Rainfall are shown in the 3 charts below.\u00a0 Each chart also contains an 11-year centred moving average which gives an idea of the underlying trend.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1585 alignnone\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1-300x143.png\" alt=\"\" width=\"617\" height=\"294\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1-300x143.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1-768x367.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1-1024x489.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1-450x215.png 450w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN1.png 1171w\" sizes=\"auto, (max-width: 617px) 100vw, 617px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1586 alignnone\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2-300x143.png\" alt=\"\" width=\"615\" height=\"293\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2-300x143.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2-768x365.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2-1024x487.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2-450x214.png 450w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN2.png 1171w\" sizes=\"auto, (max-width: 615px) 100vw, 615px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1587 alignnone\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3-300x142.png\" alt=\"\" width=\"615\" height=\"291\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3-300x142.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3-768x364.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3-1024x486.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3-450x213.png 450w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN3.png 1172w\" sizes=\"auto, (max-width: 615px) 100vw, 615px\" \/><\/p>\n<p>Standardised variables aid interpretation of data in many ways.\u00a0 If the standardised value is positive, it means that the value is above your average or expected value.\u00a0 If it is negative, then the value is below your expected value. \u00a0If the original variable is approximately normal in its distribution then the vertical scale gives us an idea of how typical or atypical each year is.\u00a0 Z-Scores in the range -1 to +1 are considered typical values and completely unremarkable.\u00a0 Z-scores in the ranges -2 to -1 and +1 to +2 are considered to be uncommon values but still entirely plausible and such values should not cause us concern.\u00a0 When Z-Scores get into the ranges -3 to -2 and +2 to +3, we should start paying closer attention and asking ourselves if something has changed especially if we get a sequence of successive points in these ranges. Finally, if the Z-scores are less than -3 or greater than +3, that is normally regarded as a clear call to action.\u00a0\u00a0There are in fact many ways of interpreting Z-Scores and\u00a0what I have said so far\u00a0merely a gives an overview of the most basic interpretations.\u00a0 A whole field of study known as <a href=\"https:\/\/en.wikipedia.org\/wiki\/Statistical_process_control\">Statistical Process Control (SPC) <\/a>is dedicated to building and interpreting such charts (known as Control Charts).<\/p>\n<p><span style=\"float: none;background-color: transparent;color: #333333;cursor: text;font-family: Georgia,'Times New Roman','Bitstream Charter',Times,serif;font-size: 16px;font-style: normal;font-variant: normal;font-weight: 400;letter-spacing: normal;text-align: left;text-decoration: none;text-indent: 0px\">For the winter of 2019, the z-scores for temperature, sunshine and rainfall were respectively +1.2, +1.9 and -0.9.\u00a0 This tells us that temperatures and rainfall were unremarkable but it was a very sunny winter, in fact the 6th sunniest on record.\u00a0\u00a0<\/span><\/p>\n<h4><span style=\"color: #008000\"><strong>Long Term Climate Trends<\/strong><\/span><\/h4>\n<p>Since the 3 moving averages in the above 3 charts all use the same units, they can be plotted onto the same chart as below.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1588 alignnone\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4-300x143.png\" alt=\"\" width=\"610\" height=\"291\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4-300x143.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4-768x365.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4-1024x487.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4-450x214.png 450w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN4.png 1169w\" sizes=\"auto, (max-width: 610px) 100vw, 610px\" \/><\/p>\n<p>This clearly shows a shift in our winter climate over the last 100 years of roughly 1 standard deviation in some cases.\u00a0 Recall that the baseline for the z-score calculation is based on the idea of &#8220;living memory&#8221; which I have defined to be the last 50 years of 1969 to 2018. \u00a0 We can characterise our winters broadly as follows:<\/p>\n<ul>\n<li>1930-1990 &#8211; we had cold, dull and dryer winters.<\/li>\n<li>1995-today &#8211; we had warm, bright and wetter winters.<\/li>\n<\/ul>\n<p>This is more or less <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-7-autumn-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">the same long term trend seen for our autumns<\/a>.<\/p>\n<h4><span style=\"color: #008000\"><strong>How many dimensions does Winter have?<\/strong><\/span><\/h4>\n<p>The long term trends chart above suggests that the z-scores for temperature, sunshine and rainfall all appear to be correlated.\u00a0 In fact this can be illusory as the above chart uses moving averages.\u00a0 If we look at the actual z-scores, we can see what the correlations are in the 3 scatter plots below.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1589 alignnone\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5-300x77.png\" alt=\"\" width=\"919\" height=\"236\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5-300x77.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5-768x198.png 768w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5-1024x264.png 1024w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5-450x116.png 450w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN5.png 1805w\" sizes=\"auto, (max-width: 919px) 100vw, 919px\" \/><\/p>\n<p>The brown square in each chart is 2019.\u00a0 Scatter plots can be useful to identify unusual years that do not follow the normal relationships.\u00a0 Here we see that 2019 was on the edge of typical historical scatters e.g. it was sunny, warm and dry which is somewhat unusual.<img loading=\"lazy\" decoding=\"async\" class=\"alignright size-medium wp-image-1590\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6-300x234.png\" alt=\"\" width=\"300\" height=\"234\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6-300x234.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6.png 384w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>Looking at the 3 scatter plots in turn, we see that sunshine is not correlated with rainfall and temperature but rainfall and temperature have a significant positive correlation.\u00a0 A statistician would look at these charts and observe that what appears to be 3-dimensional data (temperature, sunshine and rainfall being the 3 dimensions) is in fact closer to be being 2 dimensional since temperature and rainfall are essentially two aspects of the same component.\u00a0 By using <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-5-spring-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">the method of PCA (Principal Components Analysis)<\/a> which takes our 3-dimensional data set and calculates 3 new components that are statistically uncorrelated with each other, we see from the scree plot that the 1st component accounts for 1.5 dimensions whilst the 2nd component accounts for 1 dimension.<\/p>\n<p>Looking at the correlation bi-plot now, we see that the 1st component accounts for temperature and rainfall, reflecting the correlation we see in the <img loading=\"lazy\" decoding=\"async\" class=\" wp-image-1591 alignleft\" src=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6B-300x295.png\" alt=\"\" width=\"395\" height=\"388\" srcset=\"https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6B-300x295.png 300w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6B-356x350.png 356w, https:\/\/marriott-stats.com\/nigels-blog\/wp-content\/uploads\/2019\/03\/UKweatherTracker2019WIN6B.png 568w\" sizes=\"auto, (max-width: 395px) 100vw, 395px\" \/>scatter plot above.\u00a0 At the same time, the second component is just sunshine.\u00a0 The 90 degree angle between sunshine and the other two variables is again a reflection of the lack of correlation between this and temperature and rainfall as we saw above.\u00a0 This makes winter one of the cleanest seasons to use PCA and if we wanted to, we could just as easily average the z-scores for temperature and rainfall for the 1st component.<\/p>\n<p>For more information about Principal Components Analysis, please visit my link about <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/stats-training-materials-multivariate-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">training materials for multivariate analysis<\/a>.<\/p>\n<hr \/>\n<p>If you want to read <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/tag\/weather-trends\/\" target=\"_blank\" rel=\"noopener noreferrer\">my other Weather Trends posts<\/a>, please click on the link or the <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/tag\/weather-trends\/\" target=\"_blank\" rel=\"noopener noreferrer\">Weather Trends<\/a> hashtag below this post.\u00a0 Otherwise, please click the relevant season from the list below.<\/p>\n<ul>\n<li>2019 &#8211; <em>Winter, Spring, Summer, Autumn<\/em><\/li>\n<li>2018 &#8211; <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-4-winter-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">Winter<\/a>, <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-5-spring-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">Spring<\/a><em>, <\/em><a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-6-summer-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">Summer<\/a><em>, <\/em><a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-7-autumn-2018\/\" target=\"_blank\" rel=\"noopener noreferrer\">Autumn<\/a><\/li>\n<li>2017 &#8211; <em>Winter<\/em>, <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-1-spring-2017\/\" target=\"_blank\" rel=\"noopener noreferrer\">Spring<\/a>, <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-2-summer-2017\/\" target=\"_blank\" rel=\"noopener noreferrer\">Summer<\/a>, <a href=\"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-3-autumn-2017\/\" target=\"_blank\" rel=\"noopener noreferrer\">Autumn<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>The winter of 2019 was consistent with the step change in the winter climate that took place in the 1990s.<\/p>\n","protected":false},"author":3,"featured_media":1591,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[90],"tags":[48,40,72,51,46,34,47,52],"class_list":{"0":"post-1570","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-archive","8":"tag-multivariate-data","9":"tag-presenting-data","10":"tag-principal-components-analysis","11":"tag-standardisation","12":"tag-trend-analysis","13":"tag-weather","14":"tag-weather-trends","15":"tag-z-scores","16":"entry","17":"override"},"_links":{"self":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/1570","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/comments?post=1570"}],"version-history":[{"count":7,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/1570\/revisions"}],"predecessor-version":[{"id":1829,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/1570\/revisions\/1829"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media\/1591"}],"wp:attachment":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media?parent=1570"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/categories?post=1570"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/tags?post=1570"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}