{"id":1821,"date":"2019-06-06T22:57:32","date_gmt":"2019-06-06T21:57:32","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=1821"},"modified":"2020-08-03T22:13:13","modified_gmt":"2020-08-03T21:13:13","slug":"uk-weather-trends-9-spring-2019","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/uk-weather-trends-9-spring-2019\/","title":{"rendered":"UK Weather Trends #9 – Spring 2019"},"content":{"rendered":"

The 2019 spring was consistent with the step change in the autumnal climate that took place in the 1990s but was unremarkable otherwise<\/p>\n

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Meteorologists define spring in the UK to be the period from March to May so spring is now over and we are officially in summer.<\/p>\n

I analyse the long term trends in the UK weather using a statistical tool known as 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 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, please read my post on trends in the UK summer of 2017.<\/a><\/p>\n

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Latest Z-Scores<\/strong><\/span><\/h4>\n

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

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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 Statistical Process Control (SPC) <\/a>is dedicated to building and interpreting such charts (known as Control Charts).<\/p>\n

For the spring of 2019, the z-scores for temperature, sunshine and rainfall were respectively +0.9, +0.8 and +0.6.\u00a0 This tells us that whilst the season was above average on all 3 variables, it was an unremarkable spring otherwise.\u00a0\u00a0<\/span><\/p>\n

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Long Term Climate Trends<\/strong><\/span><\/h4>\n

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

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This clearly shows a shift in our spring climate over the last 100 years of roughly 1 standard deviation.\u00a0 Recall that the baseline for the z-score calculation is based on the idea of “living memory” which I have defined to be the last 50 years of 1969 to 2018. \u00a0 We can characterise our springs broadly as follows:<\/p>\n