I’ll warn you now this is a crazy post 😜. For some reason I got to wondering how much of an affect the friction from a stormy sea with large winds a big swell and large waves can have on wind speeds measured by an anemometer out in the open ocean? The reason I ask is because in the recent named storm ‘Ashley’ on the 20th of October 2024, the winds from the Weather Buoy known as K4, seemed to be rather on the low side. My memory is probably playing tricks here, but I remember when plotting any of the Ocean Weather Ships on a chart in stormy weather as an assistant, it wasn’t unusual for me to plot mean speeds of 50 knots or more. That’s when I got to wondering about surface friction and the height of the anemometer, and what effect friction would have on wind speeds? The height of the anemometer may have been 60 feet or more above the ocean surface on a weathership, but on a weather buoy, that might be no more than 20 feet. It may be fairly academic now because the days of weather ships have long since passed, but there are still hundreds of ship and probably thousands of weather buoys observations made each hour across the world, so I wonder if any adjustment at all is made to those from buoys? I did warn you that this post was crazy.😉
PS If you want to find out more about Ocean Weather Ships maintained by the Met OfficeUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy Ican recommend this great site WeatherShips.com
Christmas Day 12 UTCUTCCoordinated Universal Time or UTC is the primary time standard by which the world regulates clocks and time. It is within about 1 second of mean solar time (such as UT1) at 0° longitude (at the IERS Reference Meridian as the currently used prime meridian) and is not adjusted for daylight saving time. It is effectively a successor to Greenwich Mean Time (GMT). 1979-2023
This post is more of a reminder to myself about an application I wrote to display a grid of charts it downloads from Wetterzentrale. You can choose to display CFS, ERAERAERA stands for 'ECMWF Re-Analysis' and refers to a series of research projects at ECMWF which produced various datasets (ERA-Interim, ERA-40, etcetera). or NOAANOAANOAA is an agency in the Department of Commerce that maps the oceans and conserves their living resources; predicts changes to the earth's environment; provides weather reports and forecasts floods and hurricanes and other natural disasters related to weather. reanalysis charts either as charts of isobars overlaid over colour filled contours of 500 hPahPaA Hectopascal is the SI unit of pressure and identical to the Millibar heights, or as charts of isolines of 850 hPa geopotential heights, overlaid on colour filled contours of 850 hPa temperature. I think it produces a pretty useful grid of charts to view a month, or a season, but in truth I haven’t used it that much in the last 12 years. The example above displays surface pressure charts for Christmas day.
Winter [DJFDJFMeteorological Winter comprising the months of December, January & February] 1962-63
The grid of images above, is for daily MSLPMSLPMean sea level pressure is the pressure at sea level, or, when measured at a given elevation on land, the station pressure reduced to sea level assuming an isothermal layer at the station temperature. and daily 500 hPa geopotential heights for each day of the infamous winter of 1962-63.
The other innovative thing that I added to the application, was a colour analyser (above image). This does a lookup on the colour of each pixel across the map of the British Isles in the downloaded image, and calculates an overall average which it uses to plot a graph and fill a table with the daily 850 hPa temperature or the 500 hPa geopotential height. A crude but quite effect way of gauging just how warm or cold it is on any given day. There are problems with the app, but out of my control, in that Wetterzentrale for some years, use a slightly different resolution and size for their images. I could fix it but it’s fiddly. They also seem now not to load the ERA reanalysis images on their server. Who knows for how much longer they’ll maintain the CFS and NOAA images, it would be a real loss if this went.
I’ve added some code to my LWTLWTLamb Weather Types are often used in UK-based analyses, with individual weather patterns based on the eight primary cardinal directions (N, NE, E, SE, S, SW, W, NW) plus cyclonic (C), anticyclonic (A) and unclassified (U) types. application to display graphs of 365 day moving averages for some of the daily indices that the objective series generate. I thought it might be easier to pick out trends using an extended period like this, although the application is flexible enough to allow shorter periods. At a glance you can see that mean MSLPMSLPMean sea level pressure is the pressure at sea level, or, when measured at a given elevation on land, the station pressure reduced to sea level assuming an isothermal layer at the station temperature. over the last 10 years across the British Isles is currently at its lowest at the moment, and positive cyclonic vorticity has also been at a ten year high in 2024 as well. What it all means remains a mystery but it kept me busy this afternoon. 😜
I noticed recently that the UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy have started to publish and maintain on their website, data files of daily mean maximum and minimum temperatures from the stations that they have used to calculate the composite Central England Temperatures since 1878. I had given up hope of ever seeing this data, which gives a better insight on the machinations the UKMO go through to produce the series each day. What would Philip Eden have given to access this CETCETCentral England Temperature data! 😜 As you can see from the above screen shot above I’ve added a new viewer to my Daily CET application to download, parse and display the data in tabular form and as plotted charts.
At the moment the CET series uses temperatures from the following stations:
Rothamsted in Hertfordshire.
Pershore in Worcestershire
Stonyhurst in Lancashire.
Each of these site has a buddy site, so if it fails to report, the temperature from the other site can be used in its place. This happens a lot more frequently that I ever realised. The data files do include a file of eight boolean flags to identify which site were used for which day. The table below is for the CET values up to the 4 September 2024. I’ve highlighted the sites that are being used in the table in bold, and used grey text for those that aren’t. The provisional daily CET is in the 2nd from right column, and the difference column on the right, is the difference between the provisional mean and the one calculated from the raw data from stations being used. The difference is probably the adjustment applied to each stations temperature for the effects of urbanisation.
The table below is from 2004, and I think marks the point when Stonyhurst and Pershore replaced Squires Gate/Ringway and Malvern in the series. Whoever in the Met OfficeUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy thought temperatures from a coastal site like Blackpool was a good site to represent central England beats me, although that might be down to how Manley constructed his original monthly series. I think the Stonyhurst temperature record is second only to Oxford in England in length, and had been used for many years before this.
The latest sites all have their own peculiarities as you can see from the graph below of 30 day average daily maximum temperatures. Stonyhurst is usually the coldest of the latest three sites being used to calculate daily CET values, with Pershore usually the warmest, with Rothamsted usually trailing a little behind Pershore. All this is obviously weather dependent. So the composite CET for the warmest day in the whole CET series in July 2022 ends up being in no mans land temperature wise.
Similarly in this graph of 30 day average daily minimum temperatures from 2010, Stonyhurst is usually coldest, although the three minimum series are more closely bound than the maximum. You can see that in the cold December of 2010, Pershore is fractionally colder than Stonyhurst for a while.
The table below shows how the CET series has changed at times in recent years, and how the buddy system comes into play when temperature data goes missing.
I’ve been putting quite a lot of effort into a program I’ve developed that parses forecast data from the Met OfficeUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy weather app. I needed to do this because the UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy have just updated it to a new beta version, and in so doing have reworked all their HTML, which scuppered my old application which I developed some years ago. As far as I know there is no API that I call to access the raw forecast data with, so it’s all down to downloading and parsing a lot of HTML to extract the forecast data myself. It’s not been easy, and I’m not getting any younger, so at times it’s been a real struggle. Anyway I’ve completed most of the work now, and all that’s left is to update the numerous viewers that I use to display the forecast data in various tables, graphs and maps.
The only new feature I’ve seen that’s different in the beta version when compared to the old version is that as well as including a ‘likely’ maximum and minimum, the Met Office now also include a ‘possible’ maximum and minimum. Don’t ask me why, but it mimics what the BBCBBCThe British Broadcasting Corporation (BBC) is the national broadcaster of the United Kingdom, based at Broadcasting House in London. It is the world's oldest national broadcaster, and the largest broadcaster in the world by number of employees, employing over 22,000 staff in total, of whom approximately 19,000 are in public-sector broadcasting. do in their app.
The animated GIF is generated from a viewer that builds a bitmap image from all the available three hour forecast data for the coming week. I’ve also added maximum and minimum daily anomalies to it, as well as including an icon to show the phase of the moon and when it rises and sets.
I have a verification form which compares forecast values with SYNOPSYNOPSYNOP (surface synoptic observations) is a numerical code (called FM-12 by WMO) used for reporting weather observations made by manned and automated weather stations. SYNOP reports are typically mad hourly and consist of groups of numbers (and slashes where data is not available) describing general weather information, such as the temperature, barometric pressure and visibility at a weather station. observations. At the moment this only works for extreme temperatures, but there is no reason why this couldn’t work with wind speed, visibility and weather. So much to do, and so little time😢
Despite central England temperature series being a composite temperature from three separate sites, it’s still possible to use the UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy 25°C heatwave temperature as the threshold to calculate a heatwave day in Central England, and thereby calculate the number of three day consecutive days that have occurred there since 1878. I added this functionality to my Daily CETCETCentral England Temperature application a number of years ago, and have recently added a second method of using the maximum anomaly to do it, rather than by using a fixed temperature. At the same time I gave it all a bit of a spring clean, hopefully it’s still accurate. 🤞 The program allows you to adjust the threshold from 25°C to 30°C, and the anomaly from +6°C to +10°C, it also allows you to change the number of consecutive days from 3 to 7.
If you plot a bar chart for the number of heatwave days since 1878, as I’ve done with an accompanying 5 year centred average and linear trend, you’ll see that the number of days >=25°C has increased from 4.6 days to 10.8 days in the intervening 146 years.
The most number of distinct heatwaves (using the 25°C and three consecutive days or more rule) in a single year was six and occurred in both 1911 and 1995. The most number of heatwave days in any one year was 33, and occurred in 1976 and 1995.
The longest heatwave I found, using the 25°C and three consecutive days or more rule, was 16 days which occurred in the golden summer of 1976, between the 23rd of June and the 8th of July 1976 this was closely followed by the 15 day heatwave covering an almost identical period in 2018.
The results using anomalies are a horse of a different colour and a story for another day. Suffice it to say I used the 1878-2023 LTALTALong Term Average. This is usually defined as a 30 year period by the WMO. as a level playing field to produce the results in the table below. The year 1995 still ends up with most heatwave days of 32, and 1976 the longest run of anomalies of 6°C and higher of 16 days.
I’ve never added any animation to my Daily Central England temperature application up until now, so I thought as the weather today is still pretty dreich, I would put that right today. It’s amazing how the simple animated GIF is still going after all these years, it was declared dead many years ago at the same time as Javascript, but it’s simple and produces compact files, and there’s still not anything out there to replace it.
Apologies for the late arrival of this article. I wrote the code to identify the earliest and latest date a temperature in Central England achieved a given threshold way back in March, but I must have got fed up with it happening in 2024, so forgot all about it! In this case it was a maximum of 20°C that I was interested in, and it finally managed it this year on the 10th of May, which by coincidence is the average date it’s done this since 1878. Having said that, because this date is getting earlier, if you use a linear trend the first 20°C should happen by the 28th of April these days, so it’s really 12 days late this year. Not a lot of people know that. 😉
Anyone who is fortunate to have a Davis Vantage Pro2 AWSAWSAutomatic Weather Station as I do, know only too well, that the software it comes with doesn’t present the climate data it collects at all well. I’ve made a new unit in my VP DelphiDelphiDelphi is a general-purpose programming language and a software product that uses the Delphi dialect of the Object Pascal programming language and provides an integrated development environment for rapid application development of desktop, mobile, web, and console software. application, to graph temperature data a little more clearly. I recently came across some LTALTALong Term Average. This is usually defined as a 30 year period by the WMO. data for StrathpefferStrathpefferStrathpeffer (Scottish Gaelic: Srath Pheofhair) is a village and spa town in Easter Ross, Highland, Scotland, with a population of 1,469., I don’t think it’s been calculated from real weather data but probably derived from gridded monthly climate data the UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy make available. I mention this LTA data because it enables me to calculate anomalies, something dear to my heart. Anomalies let you gauge how the climates been performing, whether a day has been hot or cold, or a month or season wet or dry, in your own back garden.
The lower chart shows mean anomalies for the last 90 days for Strathpeffer, and clearly shows why May 2024 was a record warm month in northern Scotland. The top chart shows temperatures for the last year, and by dragging the yellow coloured box you can replot the lower graph to show the anomalies for the period you are interested. The width of the yellow box can also be adjusted with the mouse as well.
The first 20°C maximum in central England occurred on the 10th of May this year (2024), which is just about the average date for it to occur. In this ever warming world it’s gotten progressively earlier over the years. The linear trend (1878-2024) reveals that it occurred as late as the 20th of May back in 1878, but it’s now closer to happening three weeks earlier on the 28th of April. This is another new addition to my Daily CETCETCentral England Temperature application.
I’ve added another viewer, to the ever expanding list of viewers that I’ve developed over the years, to the application I use to visualise data from the daily Central England Temperature series. This one finds all the daily extreme warmest and coldest daily temperatures, highest maximum, lowest minimum, the highest minimum and the lowest maximum etc etc. As you can see in the screenshot above it consists of three data grids with a matrix of months and days to display the year the extreme occurred (left-hand grid), along with the actual value (centre grid), and the resulting anomaly (right-hand grid). In the above example I’ve highlighted in yellow any records that occurred in this decade (2020-2024) which is quite remarkable as they are still a full five years to go before it ends.
I’ve also added functionality to generate a simple animated GIF of the results in a single image.
I’ve redesigned how I visualise moving averages in my Daily CETCETCentral England Temperature program to generate a user definable moving average graph of daily CET values since 1772, this ended up being something of a job because now I dynamically plot over 250 annual ‘silver’ coloured line series, one for each year, as a backdrop. Over this backdrop I plot a 30 day moving mean for the year (dashed black), along with its corresponding +1/-1 standard deviations (dashed red and blue lines). On top of that I plot the coldest (bold blue) and the warmest (bold red) 30 day period ending 13th of April. Finally, I plot the 30 day moving average for the last 365 days (bold black with yellow outline), and at the same time I list the latest values in a ranked table on the left. With it, I make the latest 30 day mean temperature 10.57°C for the 13th of April, that’s the warmest 30 day period for that date in the series since 1772, and 3.53°C above the LTALTALong Term Average. This is usually defined as a 30 year period by the WMO. for 1772-2023. As you can see n the graph and the table this is significantly higher that the previous warmest of 9.79°C in 2017. Hopefully all this new code is producing accurate results 😉
I download the site specific NWPNWPNumerical weather prediction uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. data that resides in the HTML the Met OfficeUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy weather application requests whenever anyone looks for a forecast for a location for a number of my applications I’ve written to visualise the forecast data in a table, graph or on a map. Parsing the data was a tricky business, but I persevered, and can now grab a week of one and the three hourly data for any number of elements including temperature. As well as visualising the data, I thought it might be interesting to do a spot of forecast verification by comparing the three hourly forecast data with the actual values from SYNOPSYNOPSYNOP (surface synoptic observations) is a numerical code (called FM-12 by WMO) used for reporting weather observations made by manned and automated weather stations. SYNOP reports are typically mad hourly and consist of groups of numbers (and slashes where data is not available) describing general weather information, such as the temperature, barometric pressure and visibility at a weather station. observation for any location in the world. I know that the forecast values although quite accurate, are far from being spot on. The question I was intrigued to find out was just how accurate they are. Here are some recent preliminary results I have produced from the add-on to my UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy NWP application I wrote a number of years ago.
Notice the very warm day on the 6th of April associated with storm Kathleen, and how underestimated temperatures at Kinloss were because of a slight foehnFoehnA foehn, is a type of dry, relatively warm, downslope wind that occurs in the lee (downwind side) of a mountain range. It is a rain shadow wind that results from the subsequent adiabatic warming of air that has dropped most of its moisture on windward slopes (see orographic lift). As a consequence of the different adiabatic lapse rates of moist and dry air, the air on the leeward slopes becomes warmer than equivalent elevations on the windward slopes. effect.
Generally a pretty good result with temperatures +/- 2°C at Heathrow.
Again at Exeter temperatures within +/- 2°C of the forecast, although it didn’t do well with some of the minima, and the 8th of April was a bit of a disaster because heavy rain suppressed temperatures.
I’ve noticed that recently the Met Office are in the process of updating the NWP data their app uses, so they must have some concerns themselves about its accuracy, although the changes in the NWP might have more to do with forecast weather, rather than forecast temperatures. At the moment I am still using the old data and haven’t switched to the new trial data. In the meantime, let me know about what you think about the accuracy of the forecasts the Weather App produces in your area. I’ve still got a bit more testing, tweaking and bug fixes to do to my verification application, but I’ll keep you posted.😉
Not surprisingly, in this ever warming world of ours, the dates of the earliest and latest air frosts in Central England getting respectively later and earlier. The code behind that produced the scatter graphs below was a lot harder than I imagined. Along with the scatter graph and data grid, I also decided to add a smaller horizontal bar chart just to plot the annual distribution. The application is a lot more versatile than just finding the earliest and latest frosts and will come in useful in spotting other events in the daily CETCETCentral England Temperature series. As you can see from the linear trend in the graph below of minimum temperatures, the date of the latest air frostair frostAn air frost occurs when the temperature of the air falls below 0.0°C in Central England is now closer to the 5th of April, much earlier than the 16th it was back in 1878.
The date of the first air frost is now 11 days later on the 13th of November, rather than the 2nd of November, as it was closer to back in 1878.
For people who can’t get their heads around anomalies I’ve made a slight variation on just a simple bar chart of anomalies. The twist is that it now displays both daily temperatures and anomalies, temperatures on the left Y axis and anomalies on the right Y axis. My BBCBBCThe British Broadcasting Corporation (BBC) is the national broadcaster of the United Kingdom, based at Broadcasting House in London. It is the world's oldest national broadcaster, and the largest broadcaster in the world by number of employees, employing over 22,000 staff in total, of whom approximately 19,000 are in public-sector broadcasting.NWPNWPNumerical weather prediction uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. application downloads forecast data the BBC use in their own weather app, and parses the HTML and extracts hourly and daily forecast values for each site. I’ve kept the same scale for the extremes in each charts Y axis for each site I display in the grid to aid comparison. So you can now quickly see at a glance the forecast temperature and how it compares with the LTALTALong Term Average. This is usually defined as a 30 year period by the WMO..
I have added some extra functionality to my ERA5ERAERA stands for 'ECMWF Re-Analysis' and refers to a series of research projects at ECMWF which produced various datasets (ERA-Interim, ERA-40, etcetera). application so that I can download and access latest the ERAERAERA stands for 'ECMWF Re-Analysis' and refers to a series of research projects at ECMWF which produced various datasets (ERA-Interim, ERA-40, etcetera). 5 daily SSTSSTSea Surface Temperatures anomalies, as well as the daily 2m temperature data. SST data starts in 1979 but there’s enough of it to draw a scatter graph and see what correlation there exists between the two if you couldn’t already guess that there would be anything other than a very strong one. As you can see from the chart above my guess was correct 😜. I’ve coloured the series red for all dates after the 1 January 2023 to highlight the surge in SST in the last year or so. I will calculate and add the correlation coefficient at a later date, or as the say in this part of the world I’ll do that directly.
I’ve added a chart of 7 and a 365 day moving averages to view the sudden explosive rise in SST over the last 12 months. I would say that most charts I see bandied about regarding this rise in SST use data that is not strictly “global”, extending as the ER5 data does from 60N to 60S. I would have thought that it might be better if the global value would be more accurate if it were calculated for all oceans, regardless of sea ice. It might not be particularly scientific but why couldn’t they use a value of zero for any grid point that had sea ice present?
Now that the Copernicus program has made real-time daily global temperature data available, as well as producing daily graphs I can now also produce monthly, seasonal and annual charts by summing up the daily data. The chart above is of mean February temperatures from 1940 to 2024. The chart below is of February anomalies using the 1851-1900 baseline offset for the pre-industrial era, and shows that as well as being the warmest February on record, it also had a mean anomaly of 1.77°C above that baseline.
I estimate the first day of spring in Central England this year occurred on the 8th of February, that’s 42 days earlier than the accepted date for Spring of around March 21st depending on the exact date and time of the vernal equinox. That made it the joint seventh earliest spring in the CETCETCentral England Temperature record back to 1772. I use the average number of degree days from 1773 to 1802 to calculate a baseline to estimate the date with. Not a brilliant method. let me know if you can think of a better one. The last late spring, and the only one to occur in this century was in 2010. The linear trend reveals that springs are now arriving 24 days earlier than they did in 1772. Apologies for the late arrival of this story 😉
I couldn’t quite believe the new research by Alexandra Jahn, of the University of Colorado that claims that the Arctic could be free of sea ice by the end of this decade 😮. In her research for free of ice read 386,000 square miles, or a million square kilometres, which isn’t exactly what I would describe as “free of sea ice”. I make the date to true zero to be the 7th of June 2071 by extrapolating a simple linear trend for the last 30 years of minima. Even then the Arctic would never be truly free of sea ice I suspect. The date to the one million square kilometres mentioned in the report at the same rate would be around the summer of 2058, which looks far more realistic than the end of this decade. 😉
Now that I finally have some quality real-time global temperature data to work with, courtesy of the ECMWFECMWFThe European Centre for Medium-Range Weather Forecasts is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data., I thought that I would construct a couple of graphs you wouldn’t find in their Climate Pulse web application. The first graph that occurred to me to construct was one that plotted daily anomalies using the 1850-1900 LTALTALong Term Average. This is usually defined as a 30 year period by the WMO. as a baseline for the pre-industrial era, and overlay a 365 day moving average on it. I then overlay a 30 year linear trend over that and extrapolate a linear trend until it meets the y axis at 1.5°C. This gives a date of the 15th April 2031 when 1.5°C is reached. The IPCCIPCCThe Intergovernmental Panel on Climate Change is an intergovernmental body of the United Nations responsible for advancing knowledge on human-induced climate change.
It was established in 1988 by the World Meteorological Organization and the United Nations Environment Programme, and later endorsed by United Nations General Assembly. in contrast estimate global temperatures will exceed 1.5°C around 2040. This is what they say In their report:-
Human-induced warming has already reached about 1°C above pre-industrial levels at the time of writing of this Special Report. By the decade 2006–2015, human activity had warmed the world by 0.87°C (±0.12°C) compared to pre-industrial times (1850–1900). If the current warming rate continues, the world would reach human-induced global warming of 1.5°C around 2040.
IPCC Report
To explore the difference I have added another viewer to my application that displays a rolling 10 year mean anomaly, and then do the same as I did in the first graph, that is add a 30 year linear tend and then extrapolate it forward. This gives a date of the 8th February 2040 when 1.5°C is realised and in line with the IPCC estimate.
In light of the significant increases in SSTSSTSea Surface Temperatures in all the world’s oceans in the last year, and the resulting surge in global temperatures it may be that 1.5°C above pre-industrial levels will occur much earlier than the IPCC expected last year. As you can see using the latest global data for the 29th of February 2024 using a linear trend on a 365 day moving average 1.5°C will be reached on the 15th of April 2031, almost seven years earlier than 2040. I think using a 365 day average is much more sensitive and accurate than one based on a longer 10 year rolling average. Thanks to El NinoEl NiñoEl Niño 'The Boy' is the warm phase of the El Niño–Southern Oscillation and is associated with a band of warm ocean water that develops in the central and east-central equatorial Pacific and the surge in SST over the last 12 months, daily global temperatures have already been above the 1.5°C threshold for much of that time. A La NinaLa NiñaLa Niña is an oceanic and atmospheric phenomenon that is the colder counterpart of El Niño, as part of the broader El Niño–Southern Oscillation climate pattern. The name La Niña originates from Spanish for "the girl", by analogy to El Niño, meaning "the boy". In the past, it was also called an anti-El Niño[1] and El Viejo, meaning "the old man." event is expected later this year, this should help reduce global SST and air temperatures a little you would think, but even if and when this happens global temperatures still won’t be too far off the 1.5°C mark.
Climate Pulse is a new interactive website that’s just been released by the ECMWF. It’s a wonderful way to visualise global air and sea temperature data in graphs and in a 3D Globe. I may be wrong but the graphs look like they use the plugin from Highcharts, the globe has limited functionality compared to the graphs but is still pretty good. Web applications as good as this are gradually putting me out of a job, and although they do allow you to download the daily data as a CSVCSVA data file using Comma Separated Variable format. file, I can only match the visualisation you get in a Windows application on a PC which is already out there on the web and available to all, and that can only be a good thing.
I reworked an old application last week that I use to generate a simple six hourly North Atlantic Oscillation from NCEPNCEPThe United States National Centers for Environmental Prediction (NCEP) delivers national and global weather, water, climate and space weather guidance, forecasts, warnings and analyses to its Partners and External User Communities. reanalysis data that I download. It’s simple, nothing complicated using geopotential heights at 500 hPahPaA Hectopascal is the SI unit of pressure and identical to the Millibar or anything like that, just the pressure difference between 65N 25W and 37.5N 25W. A well as plotting the NAONAOThe North Atlantic Oscillation (NAO) is a weather phenomenon over the North Atlantic Ocean of fluctuations in the difference of atmospheric pressure at sea level (SLP) between the Icelandic Low and the Azores High. Through fluctuations in the strength of the Icelandic Low and the Azores High, it controls the strength and direction of westerly winds and location of storm tracks across the North Atlantic. I also add charts of the daily mean anomaly from the CETCETCentral England Temperature series, along with the England Wales rainfall from the daily UKPUKPUKP is a gridded datasets of UK regional precipitation. series, both of which I download from the UKMOUKMOThe Meteorological Office is the United Kingdom's national weather service. It is an executive agency and trading fund of the Department for Business, Energy and Industrial Strategy. As you can see in winter at least there is a strong correlation between the NAO and CET & UKP. I’ll add more viewers to examine the correlation, so much to do, and so little time, as the Joker said.
Daily global temperatures are still in unchartered territory and still breaking daily records in early February 2024. These two charts are a comparison between my DIYDIYDo It Yourself Global Temperature series on the left, with that from Copernicus and ERA5ERAERA stands for 'ECMWF Re-Analysis' and refers to a series of research projects at ECMWF which produced various datasets (ERA-Interim, ERA-40, etcetera). on the right. My series is based on rather crude NCEPNCEPThe United States National Centers for Environmental Prediction (NCEP) delivers national and global weather, water, climate and space weather guidance, forecasts, warnings and analyses to its Partners and External User Communities. reanalysis 2.5×2.5 gridded data, whilst ERA5 is based on reanalysis data over a much finer 0.1×0.1 grid I believe. The biggest difference is the estimates of the global temperature, my DIY series being around 9.4°C, whilst the ERA5 is 13.5°C. But the shape of the daily temperature line series are quite similar if you take a closer look even though the DIY series is based on a much coarser grid.
Another day another application. This time a viewer to display ERA5ERAERA stands for 'ECMWF Re-Analysis' and refers to a series of research projects at ECMWF which produced various datasets (ERA-Interim, ERA-40, etcetera). daily global temperature data from Copernicus. So much talk at the moment about how the daily temperatures have been exceeding the 1.5°C threshold a goal that was set in the Paris Agreement’s long-term goal of keeping warming “well below” 2C and aiming to limit it to 1.5C“. As you can see that hasn’t been happening much in the last year, to say the least. The ERA5 data only extends back to 1940, so finding, or more correctly guessing at what the LTALTALong Term Average. This is usually defined as a 30 year period by the WMO. was for the series between 1850 and 1900 was vital to get an accurate anomaly from the pre-industrial age. Reading between the lines of an article I found on the on the Copernicus website I came up with the figure of 0.9°C. That’s the difference between the 1851-1900 and the 1991-2020 LTA and the offset I’ve applied to the first and the third graph in this article. It’s not specified anywhere that I can find that this is what it is, but it’s my best guess.
As you can see the 365 day (leading) running mean has now also exceeded 1.5°C.
The program can also display daily data from the Arctic and Antarctic, Northern and Southern Hemisphere, and the Tropics. Still some work to do on it and some new ways to display the data but that’ll have to do for now.
Again I would like to thank Professor Eliot Jacobson for giving me the link to the raw data on the Climate Reanalyzer web site, and of course to ECMWFECMWFThe European Centre for Medium-Range Weather Forecasts is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data. and Copernicus for generating these global estimates from their reanalysis data in the first place.
