torsdag, juli 22, 2010

State of climate

This article will argue the following:
  • The sun and orbiting parameters (PDF) are primarily responsible for climate change. 
  • The magnetic activity of the sun is in all likelihood the primary cause of modern global warming, implicitly rendering statements of 'a discernable human influence' practically null and void, pending the outcome of real world experiments such as CERN's CLOUD project.
  • Arctic melt and freeze episodes are modulated by solar irradiance governed by cloud albedo, as well as snow and ice extend.
  • Mainstream climatology has a good deal of the causality upside down, which bars us from insight into the mechanics of the glacial and interglacial periods, the monsoons and the spawning of tropical cyclones.
  • For the same reasons, we have difficulty understanding the importence of ocean circulation, such as ENSO, PDO and the Golf Stream.
  • We will experience cooling for the next 20 - 30 years.
  • La Nina conditions in the Pacific will likely persist for 3 - 4 years

    In the beginning there was light:

    Recently I stumbled upon an article (PDF) in a paper called Astronomi, where a Norwegian astrophysicist claim to have observed a neat correlation between surface temperatures in Norway and the length of the previous solar cycles:
    Solen varsler et kaldere tiår

    Jan-Erik Solheim, professor (emeritus) ved Institutt for teoretisk astrofysikk, Universitetet i Oslo, har forsket på sammenhengen mellom solflekkperioder og temperaturer i Norge. Denne forskningen er et originalt arbeide som først publiseres i Astronomi.

    Jo lenger en solflekkperiode varer, jo lavere er middeltemperaturen for utvalgte steder i Norge i den neste perioden. Det viser beregninger utført av norsk astrofysiker, som varsler om et kaldere tiår.

    Av Jan-Erik Solheim

    Solheim, means 'sun home' in Norwegian a rather odd coincidence - is it not?

    The article provides us with this table:
    Solar cycles
    Start year
    I was wondering if this supposed correlation would show up on the global scale. So to put this theory to the test, we quite simply plot a graph with the previous cycle length value at each cycle end. To follow the intuitive perception, that the curve should rise and fall with temperatures I inversed the Y-Axis scale, so that the higher the value of the cycle length the lower the curve will go and vice versa. That method should reflect the logic of the argument as I percieve it. I then plotted that graph and the GISS mean global anomalous temperature dataset and added some trend lines.
    This was the result:

    Now, I'm admittedly not a statistician by occupation (or heart - for that matter), but for what it's worth: that seems to me to be a near perfect correlation. Especially, when taking into account the corruption of the GISS dataset.  Probably an artifact of James Hansen's mission to save the world. 

    Please compare the trend with these
    NASA GISS US land temperature anomalies after the adjustments
    (PDF) in 2007:

    While concidering the implications of the graphics, please also review the following reportings of the past:

    Warming Arctic Climate Melting Glaciers Faster, Raising Ocean Level, Scientist Says - “A mysterious warming of the climate is slowly manifesting itself in the Arctic, engendering a “serious international problem,” Dr. Hans Ahlmann, noted Swedish geophysicist, said today. - New York Times, May 30, 1937 

    Then 33 years later:   

     “The United States and the Soviet Union are mounting large-scale investigations to determine why the Arctic climate is becoming more frigid, why parts of the Arctic sea ice have recently become ominously thicker and whether the extent of that ice cover contributes to the onset of ice ages.” - New York Times, July 18, 1970 

    US temperatures according to Hansen et al 1999 (fig 6)

    And then again 38 years later: 

    Arctic warming has become so dramatic that the North Pole may melt this summer (2008), report scientists studying the effects of climate change in the field. “We’re actually projecting this year that the North Pole may be free of ice for the first time [in history],” David Barber, of the University of Manitoba, told National Geographic News aboard the C.C.G.S. Amundsen, a Canadian research icebreaker. - National Geographic News, June 20, 2008

    Compare that statement to this National Geographics sketch (PDF) 32 years earlier.

    The Arctic has a natural habbit of warming up and cooling down on a decadal timescale, as global temperatures rise and fall. That is: it rises and falls conciderably in the real world, but in a certain branch of climate science it never happened.

    A new dark age:

    And some have been quite busy constructing a very persuasive revisionism, depriving the world of much of what was previously concidered knowledge: a massive campaign effort, which features some of the most Orwellian distortions I have ever laid my eyes on - and in my day, I've seen a few. After the IPCC 1995 report, followed by the 2001 report, history, it would  seem, has been rapidly rewritten: As present temperatures failed to rise, the temperatures of the past went down!

    The infamous hockeystick of IPCC's 2001 report:
    Now, I realise, that science must change it's paradigms once in a while, that just comes with the territory, but I think it evident, that some in our case have gone above and beyond the call of duty. It's the interpretation of data, not the manipulation of data, which should seed new paradigms. But it is - I think - important, that we all realise how tempting it can be to nutch the whole thing a little, so that you can have it your way. This is after all the reason, that we lie: to have it our way. Deception (PDF) is the gray area of our minds, once you venture there, you might find yourself lost, and trapped, inducing a pseudo state of paranoid psychosis: transforming 'abominal' perceptions to fit the concieved 'reality':

    Graph from IPCC's (PDF) report in 1990 (FAR): 

    On the one hand, as scientists we are ethically bound to the scientific method, in effect promising to tell the truth, the whole truth, and nothing but – which means that we must include all doubts, the caveats, the ifs, ands and buts. On the other hand, we are not just scientists but human beings as well. And like most people we'd like to see the world a better place, which in this context translates into our working to reduce the risk of potentially disastrous climate change. To do that we need to get some broad based support, to capture the public's imagination. That, of course, means getting loads of media coverage. So we have to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts we might have. This "double ethical bind" we frequently find ourselves in cannot be solved by any formula. Each of us has to decide what the right balance is between being effective and being honest. I hope that means being both. 

    Stephen Schneider

    You may call it ethics, I call it politics. And in some cases I would even concider it, criminal. There is something deeply flawed at the bottom of all of this, which is revealed in Schneiders line of thought. At the very least it serves to put a perspective on the following observations: 

    In brief, from the age of enlightenment we have emerged into the philosophy of post-modernism which sets aside evidence as the authority and asserts that the ‘truth’ is what you believe – if you believe it, then it is your ‘truth’. Importantly all opinions are to be given equal authority irrespective of where the evidence may lie. These ideas have progressed to what is now called ‘Post Normal Science’. This holds that science is subservient to the story that must be told. The role of science is no longer about discovering new ‘truth’ but supporting the ‘story’ which is perceived to be the truth. This gives rise to the notion of “noble-cause science”, which allows scientists to ignore contrary evidence, or worse, manipulate the evidence, if the cause is noble. We have seen evidence of this in the climate change debate.

    Doug Edmeades 

    Quoted from the article: Closing out dissent - by Bob Carter... a very interesting read.

    One would be blind, if one failed to notice the resemblance to religion in all of this: End of days, soothsaying (PDF), blasphemy, guild, payments and sacrifices to enable the congregation of blessed men - who may yet save the day, and our polluted souls. In it's essence: an anti-science masquerading as science.

    Returning to the subject of the sun:

    I chose the year 2021 for the end of cycle 24. No one knows of course how long it will actually be, but quite ominously it's had a very slow start. Furthermore the length of cycle 23 seems to be somewhat disputed. Here's the closest to an official statement, that I could get:

    May 8, 2009 -- Solar Cycle 24 Prediction Update The Solar Cycle 24 Prediction Panel has reached a consensus decision on the prediction of the next solar cycle (Cycle 24). First, the panel has agreed that solar minimum occurred in December, 2008. This still qualifies as a prediction since the smoothed sunspot number is only valid through September, 2008. The panel has decided that the next solar cycle will be below average in intensity, with a maximum sunspot number of 90. Given the predicted date of solar minimum and the predicted maximum intensity, solar maximum is now expected to occur in May, 2013. Note, this is a consensus opinion, not a unanimous decision. A supermajority of the panel did agree to this prediction .

    Now, compare that with the following statement:

    Dec. 21, 2006: Evidence is mounting: the next solar cycle is going to be a big one.
    Solar cycle 24, due to peak in 2010 or 2011 "looks like its going to be one of the most intense cycles since record-keeping began almost 400 years ago," says solar physicist David Hathaway of the Marshall Space Flight Center. He and colleague Robert Wilson presented this conclusion last week at the American Geophysical Union meeting in San Francisco .

    Red in the face? - That can most probably not even begin to describe it...

    Well, researching the subject of solar influence I encountered, this video, with Jasper Kirkby, a declared heretic and sceptic of the global warming gospel, as well as the head of the CERN experiment CLOUD, which results by the way the world needs desperately to hopefully resolve the climate issue, probably much to the disadvantage of the influential elites who have invested heavily in the global warming scare. To what lengths these people will go to protect their valuables (their means of power) I have no clue, but I surely expect it to turn ugly one way or another.

    In the video, Jasper's slide show and indeed Jasper himself states, that cycle 23 was 13,1 years in length. Observing the graph to the left (which has the same origin as the above resolution of the 12,6 number) with a cursory glance, one might actually get the impression, that cycle 23 extends well into 2009. Can someone knowledgeable cast a light on this issue? I find my self at a loss...

    The issue is obviously important, and not nit picking: if the cycle was actualy 13,1 years in length, that puts us close to the Little Ice Age category, which could potentially have devastating consequences, albeit such speculation is completely refereed by the actual state of future events. The experiment is forever ongoing, though, this fundamental scientific guideline seems to have escaped the attention of quite a few of our high and mighty, not to mention the allegedly brightest to the exclusion of some.

    A clouded view on things to come:

    I'll try to make the rest short, so those of you who do not know simple climate science will probably loose track of me here:

    If the CLOUD project is able to illuminate the approximate state of affairs to the advantage of the theory of cosmic rays (and this is where I put my money), that would provide us with a simple trigger for decennial and centennial scale climatic changes and I would then suggest the following idealised causality:

    A reduced cloud cover - as a result of an active sun - in the polar regions will reduce albedo and warm the ocean waters in turn melting more ice and warming more water. This has the effect of lowering the pressure of the polar cell effectively shifting the polar front to the north (south). In the terminology of those supposedly in the know, I believe the concept would be phrased: a weakening of the meridional pressure gradient. As the polar cell retreats, the Ferrel cell in turn moves north (south) raising the tropopause and hence reducing the steepness of the thermocline. In this schematic the obvious consequence will be a lower pressure in the meandering of the polar vortex, which in the inverse scenario would otherwise lend assistance to the Hadley circulation in the tropics. This tiny shift in the meridional pressure gradient, would thus work to weaken the trade winds.

    Following the logic through, this in turn ought to weaken zonal transport dictating the volume of equatorial waters transported to the north at the plate boundaries in the west, as well as the volume of upwelling at the eastern boundaries. All of these schematics produce the net effect of conserving both mass and energy in the tropics, as well as reduce cooling from the upwelling sites. As the polar regions now receive less mass/energy the pressure in turn rises, and the heat in the tropics serve to lower the pressure, producing conditions of the opposite sign. As conditions reverse the polar regions again heat up and the tropics cool.

    Point being: the magnetic activity of the sun could have an indirect modulating effect on the meridional mass/energy transport engine by weakening zonal and hence meridional transport of ocean waters such as the Nino circulation in the Pacific and the Golf Stream in the Atlantic. When the sun relaxes La Nina and positive NAO conditions will be slightly more predominant. If conditions persist over long time scales, the surface waters of the tropics will become much colder as a result of an enhanced upwelling regime, and will have a difficult time raising temperatures and hence lowering pressures in the polar regions. In this state the enforced polar cells acts to drain the system of energy by delivering moisture to glacier areas in the north - spawning glacial events.

    My causality, which should be so glaringly obvious, that it is dumbfounding to realise, it is actually not being popularly proposed, explains rather well the heatings and coolings to the rhythm of the sun. It even explains what happens during ice ages, where the millennial scale radiation modulations are primarily dominated by orbital parameters. Another heat budget modulater is the density conditioning, determined by long gone past events, of the thermocline at the equatorial upwelling sites - an ocean memory interface. In a world where the plates do not interfere with equatorial throughflow, this cannot happen! Which explains rather neatly, why the world started cooling 20 - 10 million years ago, first with the final demise of the ancient Tethys and secondly 3 million years ago (PDF) with the closure of the central American throughflow. I realise that the cooling dates back further, but those episodes do not much relate to the equatorial throughflow (though the Indian plate movement might be an exception), and must be reserved for a future discussion.

    If anyone has ever actually proposed the above causality schematics in short and precise  language, I apologize: I have simply never encountered such an explanation in plain English.

    The quiet ocean:

    While on the subject of La Nina I remembered some data, that I have been looking at. Now this might be interesting, so I'll elaborate a bit further. First let's look at some comparison data for the last decade since the great El Nino in 97:

    This data, to my mind, speaks volumes as to the causality I previously suggested. First: they show correlation between global mean sea surface temperatures and the NINO3.4 region. No other Nino region express this clear correlation - I've checked. Second: while on the average Nino temps have been going down slightly, global temps have been going up slightly since the 3 years long La Nina blew around the beginning of the millennium. In fact they have just cross sectioned, which indicates to me, that the heat has been moved out of the tropics in consistency with a negativ PDO pattern.

    More data on the Nino regions:

    They all show cooling, except for region 4, which has recovered quite a bit since the La Nina 2007 - 2008. As the graf to the left will show you, the cooling is highest in the east in the Nino 1 & 2 regions - by a full average degree.

    Well here's the interesting bit: according to NOAA numbers the anomallous temperatures during last winters El Nino was 0,7 degrees lower, than the El Nino of 97 in the 3.4 region.

    This article (PDF) illuminates the subject of model capabillity in the face of predicting Pacific circulation events, if I may quote: 
    Nino regions:
    Attempts to use fully coupled non-linear GCMs to simulate and/or forecast El Ni˜no have been less successful, unless constrained by sophisticated data assimilation techniques and run for short forecast periods, over which equally sophisticated analysis techniques are used to correct for well-documented “model drift.” This model drift is essentially a reflection of the fact that the coupled GCMs produce a “climate” that is not sufficiently close to reality.

    The article is from 2005. Now, would anyone care to explain to me, how, on the basis of such blatant ignorance, the IPCC finds, that it could by 1995 primarily ascribe the temperature anomalies of the modern age to man? The short and firm answer to my mind should be obvious: They couldn't possibly do so! - They quite simply have little to no clue about the modulating factors of tropical Pacific SST's, so that it is in fact impossible to make statements about the 'discernable influence' of man with any confidence, whatsoever. If the IPCC crew had been real honest scientists of mind, and not politicians by heart, it would have all ended there, with that simple question!

    And the authors of this article are not just a bunch of idiots walking in from nowhere. I provide you with a list, for your convienence: 

    William S. Kessler
    James N Moum 
    Daniel L. Rudnick
    Meghan F. Cronin
    Paul S. Schopf
    LuAnne Thompson

    This state of affairs has not been communicated to the general public. Constituting a failure in the medias role as sceptic watch dogs, and probably reflecting, to a certain degree, a popular mindset, which has been instilled ever so thoughroly, as a result of the rapid cooption of the environmental mythology, by influential and fairly ignorant circles, from where it is being preached as indisputable.

    The ages of the ice:

    Recalling the earlier reports on Arctic meltings and freezings  from the years 1937 (melt), 1970 (freeze), 2008 (melt) we may cast a glance on the graphics below:

    Now, we've got to be very carefull with the enterpretation of this graphics, because something lies hidden here and does not immediately leap to mind.

    On the contrary: One might indeed, from a cursory glance, quickly conclude that the freeze and melt is dictated by the cycles of the AMO. But that does not really explain anything - at least not to my mind, and it's not for a lack of trying. All things being equal, why would the Atlantic exhibit these mood swings? I simply couldn't come up with the causality, no matter how much I tried. Also, studying the graphics one might get the idea, that the AO beats to the pulse of the PDO, but this would be equally wrong, for the very same reason: there is no clear causality to explain, why the Pacific would have these wild mood swings.

    But then in a lightening of rare insight it hit me: The AO has to be the driver of this rather well documented behaviour:

    The correlation between the AO index and SST for the period 1900–1998 shows that the AO is related to a coherent large scale Northern Hemisphere SST pattern. High values of the AO index are associated with positive SST anomalies over the central and western part of the North Pacific, the western subtropical North Atlantic and the western coast of Europe, while negative anomalies dominate the entire tropical region, the west coast of North America and southwestern Greenland. Approximatly, regions are significant above the 95% (90%)-confidence level when the correlation exceeds ±0.2(0.15). [G. Lohmann et al.]

    And the same must be true of the Antarctic!

    It should by now be quite apparent, if we look at the graphic from the perspective of the arguments presented in this article, that the Arctic warm episodes are most extreme in the transition to the negative phase of PDO and vice versa. We live in a world, where the seemingly small differences in the pressure gradient between the equator and the poles in times of lessened solar irradiance can send the trade winds into a frenzy (La Nina and NAO+), because the meandering of the polar vortex will be lower in temperature and thus higher in pressure, hence driving the hot tropical waters into the polar regions, where the mass/energy form clouds and is expended as ice melt and precipitation in the form of snow in mountain areas increasing overall albedo, all the while driving cold upwelled waters in their wake cooling the tropics. In the end cooler and cooler waters will reach the poles.

    The solar irradience at the poles is governed by the albedo (snow, ice and clouds) and the orbital parameters. Lowering the irradiance in the north will over long time periods serve to lower the overall heat contents of the world oceans. A higher irradience will tend to slow the trade winds and conserve heat in the tropics (El Nino, NAO-).

    What's more and much worse: Climatologists have now completely fallen prey to the popular perception, that some inept personalities in their own ranks have served to spawn: that the so called Great Thermohaline Conveyor is the apparent blessing of the world.

    But this perception is the child of misconceptions:
    • The conveyor is not driven by density, which only determines stratification. It's driven by wind which creates a pressure differential in the oceans. Think about it: Why would the sinking waters turn south (north)? There can only be one explanation to that question: because water is being displaced by the trade winds in the tropics and must be replaced; the water turns south because it's being dragged by a vacuum (from the perpective of water) - a more accurate description might be dynamo or vortex, though it's admittedly rather more difficult to comprehend, when visualising the Golf Stream.
    • Thus, it is complete nonsence to suggest, that the conveyor should stop operating for any other reason, than that the winds should stop blowing - or reverse, when crossing the equator due to lessened convection at the upwelling sights, generating conditions of higher pressure at the ITCZ (InterTropical Convergence Zone). This is what incidentally drives the monsoons and the tropical cyclones.
    • In and so far salinity acts as a modulator it's precense serves to determine how much mass/energy is delivered to the atmosphere. The higher the salinity of water, the lower the time interval before it's stratified to the depths by mixing and convection, thus the energy/mass exchange with the atmosphere will have a shorter duration (which is just one way of putting it). This in turn modulates the temperature at the upwelling sites in the far distant future.
    • During La Nina conditions water is delivered in the form of precipitation  from the Atlantic to the Pacific serving to increase the salinity of the North Atlantic, thus lowering the  mass/energy exchange with the atmosphere at higher latitudes, where seawater is less salty, in effect strengthening atmospheric pressure but also lowering albedo, as well as warming upper layers of the arctic ocean preserving some sort of delicate pressure balance. As the sun shyes away from the polar regions as a function of orbital parameters it compensates to a lesser degree the tendency toward cooling, spawning more transfer of mass/energy from the tropics as a function of the Vortex meandering lending assistance to Hadley Circulation. If this transfer is not at any given time suffient to make up for the loss of energy from solar irradiance, the process will accelerate producing: colder waters from the upwelling sites in the tropics, thus in effect lowering the temperatures of the waters eventually arriving at the poles. This will also serve to modulate the convective processes in the tropical North Atlantic gyres lowering the mass/energy exchange with the Pacific Cold Tung and hence the salinity contents. As the temperature and salinity differences between the tropical and polar waters narrow, the contact time with the cooling atmosphere is slightly prolonged, producing more clouds, precipitation and cooler ocean waters in time spawning glacial events.
    • Naturally the described processes also serve to modulate CO2 overall uptake and release.

      In the end:

      If I have grasped anything, whatsoever, the polar regions have quickly recovered pressure from a low caused by the 2007 - 2008 La Nina, this is not good news. So if the sun remains the lame horse, that it is at the moment, the La Nina which seems to be evolving in the Pacific all things considered should blow for 3 to 4 years. This will in the short run cause some polar melt - nothing, however, in the magnitude we have witnessed so far - but it will also serve to expend the remaining fumes that we're warmed by at the moment. Much of that expenditure, should go into a substance, which at least will keep the kids happy. :-)

      So, expect to see more of this shortly:


      torsdag, juli 08, 2010

      Macros to handle Excel time series

      I was looking at some climatological indices like SOI, NP, AMO, NAO, DMI and some solar stuff as well, but also things like GISS's global temperature anomaly table. Best way to do that really - unless you're truly weird - is to load the indices tables into a program like Excel and run them through the diagram wizard. I have Office 2003, and there are some nice options to play with:

      You can plot comparable diagrams with two Y-axes, and compute running means, linear trends and polynomials for phasing analyses , which are all nice things... I ran into a problem however, and it goes sort of like this:

      If you have a 2D table like this one:

                            Jan                Feb
      1880              -1                  1
      1881              -2                  2

      Then Excel will plot it as separate time series on the same time line; which means that you will get two coloured curves: 1 for January and 1 for February. If someone knows of a way where you mark up that data and get Excel to plot one curve with 4 data points then I would very much like to hear about it! - I have looked high and low, not finding a clue that someone would even consider this an issue.

      Now the problem, which may be only mine, because I'm an idiot and haven't seen some obvious light in sky can be remedied, at a cost, depending on your solution. What you can do is:

      1) Accept the garbage that Excel will actually feed you, which renders a coherent trend analyses a practical impossibility.

      2) Compute a mean value by month or year and then plot that, which effectively removes outliers and hence some things of interest.

      3) Rearrange the data so that they look something like this:

      1880 Jan -1
      1880 Feb 1
      1881 Jan -2
      1881 Feb 2

      Indeed, out there on the web, some of the data actually comes in this format, but it is a rare phenomenon.

      Anyhow, if you're into trend analysis and spotting all that odd stuff in the data, what you'll want to reach for is that third option, except: you must now face the gruesome reality of hours of labour rearranging a table stretching from say 1856 to 2009, and then realise you have 10 - 15 of those.

      Imagine my horror: after days of searching for an automated way of doing this, to come up completely empty. Well, not entirely completely, although for most people it would have been; I actually came up with a somewhat practical solution: all I had to do was program an algorithm in Visual Basic to do the trick.

      Now, for a lot of people this is clearly not the option, that they would choose, but fortunately I have some programming experience; indeed I have previously programmed more difficult solutions than this one, albeit that coding was done in Basic, Pascal and Java, but Visual Basic looked at first glance like a mix of those languages, so why not give it a go? - After all I only had to learn the basics.

      And I'll even share my hard work with all of you, just in case some poor soul have the same problem, and as of yet, has not solved it - all because I believe in that sort of thing - sharing, that is...

      But I must briefly return to the beginning, because in order to produce this problem for myself in the first place, I had had to solve another problem: Often times data indices are served cold on the web, that is: in the shape of plain text tables; if you copy paste those to Excel initially all you'll get is garbage, however, if you keep the selection selected after pasting and choose the Text to Column option in the Data menu, you'll get acquainted with a nice wizard which solves that problem neatly - it can even convert a period notation to a comma notation and vice versa.

      Well, now that we know how to quite easily convert all those nasty text tables into something that Excel can actually plot, we'll naturally be or not be more interested in what was originally, and likely ultimately, only my problem.

      Let's start with the simple part:

      Sub ManyToOne()

       Dim z, x, y As Double

       For y = 2 To Selection.Rows.Count
        For x = 2 To Selection.Columns.Count
         z = z + 1
         Sheets("Makro").Cells(z, 1) = Selection.Cells(y, 1) & " " & Selection.Cells(1, x)
         Sheets("Makro").Cells(z, 2) = Selection.Cells(y, x)
        Next x
       Next y

      End Sub

      Of course, this is as simple as it gets. Though I will not bother you by explaining the actual mechanics, I can tell you, that this small algorithm will convert a 2D table into the single column (or row) like structure required by excel for a contiguous time series, and as suggested in solution 3.

      Create a macro with the dialog boxes in the Functions menu. In the editor paste the above replacing all other text. Insert a new Spreadsheet called: Makro. This is important, because the algorithm will only output to a spreadsheet called Makro, unless you change that in the source code.

      Now, find yourself a nice 2D table in a format like the one I showed in the beginning. Mark up everything in a box: years, months and the data itself. You have to be precise with your selection or something might crash. Run the macro from the Functions menu, and then go to the Makro spreadsheet to view the result. You can now plot all the data in a single series.

      Using settings in the Functions menus dialogs you can even assign a shortcut key to the macro.

      If you prefer rows to columns select everything, copy it, and right-click on a cell to the right of the table columns, choose paste-special from the menu and tag transpose in the dialog - click . The columns are now inverted to rows.

      And now I wonder, wouldn't there be at least one person maybe even two, out of all the people in the world, who would lean back in an arrogant posture and say something like: Well, that's very neat of you, but that was an easy trick; what if I wanted to go the other way around? You said yourself, that the data sometimes come in the format we now got, but isn't there something to be said for the 2D format?

      And that might very well be so, so here it is:

      Sub OneToMany()

       Dim z, y, x, tx, bx As Long
       Dim t As String
       Dim m As Variant

       m = Array("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")

       y = 2
       x = 1

       For z = 1 To Selection.Rows.Count
        t = Selection.Cells(z, 1)
        tx = InStr(1, t, " ")
        While tx > 0 And tx < 5
         t = Mid(t, tx + 1, Len(t) - tx)
         tx = InStr(1, t, " ")
        If Len(t) > 4 Then t = Left(t, 4)
        If z = 1 Then Sheets("Makro").Cells(y, 1) = t
        If z > 1 And Val(t) <> Val(Sheets("Makro").Cells(y, 1)) Then
         If bx < x Then
          For tx = 0 To x - 2
           If tx < 12 Then Sheets("Makro").Cells(1, tx + 2) = m(tx)
           If y = 3 Then
            If bx > 1 Then
             Sheets("Makro").Cells(y - 1, x - tx) = Sheets("Makro").Cells(y - 1, bx)
             bx = bx - 1
             Sheets("Makro").Cells(y - 1, x - tx) = ""
            End If
           End If
          Next tx
         End If
         y = y + 1
         bx = x
         x = 2
         Sheets("Makro").Cells(y, 1) = t
         x = x + 1
        End If
        Sheets("Makro").Cells(y, x) = Selection.Cells(z, 2)
       Next z

      End Sub

      See, that's programming I like!

      Even though this algorithm assumes a data format that goes something like this: [1880 1] or [1 1880] it can handle some deviation from that assumption. It will provide up to 12 months a year, but if your data are 3 months means or even weekly or daily means you can ignore that, and set up your own stickers when the routine is done. It does require labels though, that are 4 characters long, like 1881 to identify each unique column. A label as a whole can be longer than 4 characters if its individual components are separated by spaces (and only spaces). It's imperative however, that the unique identifying component be 4 characters or digits wide, and that no other component be more than 3 characters or digits wide. If you use wisely the Text to columns wizard in the Functions menu when you have pasted a plain text table into Excel, you should be able to provide the algorithm with a format it can work on.

      Sometimes these tables come with only the last months of the first year and the first months of the last year, the algorithm will account for such a possibility.

      When all that's said and done, be aware, that this algorithm runs on a set of assumptions, which are not always true, and that it can and will return garbage if you do not handle it according to above specifications.

      If you want to set up a timeline which it can handle without any problems the following algorithm will do the trick:

      Sub YearMonthSeries()

       Dim m As Variant
       Dim i, a, y As Integer
       Dim s, e As String

       m = Array("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")

       s = InputBox("Input start year", "Time Series")
       e = InputBox("Input end year", "Time Series")

       For i = Val(s) To Val(e)
        For a = 0 To 11
         y = y + 1
         Sheets("Makro").Cells(y, 1) = Str(i) & " " & m(a)
        Next a
       Next i

      End Sub

      That's all folks! Hope I've been helpful to one or two people...