Claim: Climate changes make some aspects of weather forecasting increasingly difficult

Stockholm University

The ongoing climate changes make it increasingly difficult to predict certain aspects of weather, according to a new study from Stockholm University. The study, focusing on weather forecasts in the northern hemisphere spanning 3- 10 days ahead, concludes that the greatest uncertainty increase will be regarding summer downfalls, of critical importance when it comes to our ability to predict and prepare for flooding.

The study How Global Warming Changes the Difficulty of Synoptic Weather Forecasting by Sebastian Scher and Gabriele Messori at the Department of Meteorology, published in Geophysical Research Letters, establishes that our ability to make accurate weather forecasts is affected by the current changes in the global climate. A major factor is the decrease in the temperature difference between the North Pole and the equator.

In the studied span of medium-range weather forecasting (3-10 days) the most prominent uncertainty seems to befall the ability to predict the volume of summer rain. Certain other parameters, such as temperature and air pressure, are on the other hand likely to become more accurate.

“Reliable weather forecasts are tremendously important for almost all of society, and summer flooding in the northern hemisphere especially is one of the great challenges as the climate is getting warmer” says Sebastian Scher, main author. “It is very important that meteorological institutes around the world are given the opportunity to develop their tools and methods as conditions change.”

The research project at Stockholm University will continue, during the next step specifically focusing on the ability to predict heavy summer downpours in 24-48 hours.


How Global Warming Changes the Difficulty of Synoptic Weather Forecasting is available here:

Public Release: 22-Mar-2019

From EurekAlert!

100 thoughts on “Claim: Climate changes make some aspects of weather forecasting increasingly difficult

  1. “the most prominent uncertainty seems to befall”…their excuses for not being able to predict anything

    The science is right….it’s climate change making it inaccurate

    • Gee, Weatherbell is still able to do a real good job forecasting based on history and pattern recognition of the MJO and SOI. Perhaps the climate change based models suck?

      • That’s what I’m thinking. I believe it’s pretty hard take credence with people who admittedly can not predict the weather 3 to 10 days in the future but unaqivacally can predict the weather 10 to 80 years in the future. According to predictions from years ago the oceans should already be flooding most of the coastlines and it should be so hot that most life on earth should have ceased to exist. All of there predictions to date have not come to fruition why would anybody in there right mind believe any future predictions they have?

    • “Reliable weather forecasts are tremendously important for almost all of society, and summer flooding in the northern hemisphere especially is one of the great challenges as the climate is getting warmer”

      Reliable weather forecasts are a fantasy. Especially using computer models.

      • Exactly , the main problem in making accurate forecasts is that they have got rid of most of the experienced meteorologists who had a career of experience of actual local weather behaviour, and replaced them by defective computer models.

        Just like flying a plane gets harder when some dumb-assed AI thinks it needs to push the nose down and an experienced pilot knows it is wrong but can not get full control of the plane.

        • Exactly , the main problem in making accurate forecasts is that they have got rid of most of the experienced meteorologists who had a career of experience of actual local weather behaviour, and replaced them by defective computer models.

          I agree, the loss of experienced meteorologists would most likely result in less accurate forecasts simply because any recently (past 5-10 years) acquired College training of/for “weather forecasting” has surely trained the students to be dependent upon “computer generated forecasts/models” ….. rather than their acquired ……. common sense thinking, logical reasoning, intelligent deduction and/or “gut feelings”,

    • I reported in a comment on WUWT maybe a decade ago that I had noticed forecasts in our area more often than not were a couple of degees or hotter than the actual and I did an experiment in which I took the 7 day and 14 day forecasts and subtracted a degree off their highs and after most of the summer, found my “predictions” were better than theirs. I sent a letter to the forecasters telling them this but got no reply. I believe they factored in warming and this was in the middle of the two decade “pause” that hadnt yet been acknowledged.

      • rain downfall … surely you still can measure relative humidity. I think the problem is their temp forecasts are too high because they are expecting them to be warmer. Let me help here. We are heading for cooler weather as the expected El Nino isnt going to be a performer – too much cold ocean water around the globe and notably around Scandinavia. Expect a rainy spring and summer this year in Stockhom.

      • Let me give you a dirty little secret about verification of forecasts. I did the verification for NAS Fallon NV for a couple of years when I was in the navy. The verification is based on what is recorded at the observation site. Which is at the most an acre in size. If five miles away it is 10 degrees higher it doesn’t count. If you didn’t forecast rain and it rained everywhere but at your recording station, your forecast still verified. Temperatures over a forecast zone can vary wildly. If the high or low temperature was within 5F of the forecasted temperature it was counted as verified. Example: On very hot days in PDX (meaning 100+) the official recording site at PDX airport will be 5-10 degrees cooler than the rest of the city because it is only 1/4 mile away from the Columbia River. Their forecast is based on what they think their recording site will record.

        Truthfully, you can’t get better than 5deg, there are too many local factors which can’t be accounted for. If you can spend the money for an extremely accurate thermometer you will discover that the temperature can change up to five degrees within a couple of minutes, sometimes for reasons that cannot be discerned.

  2. Now, it is making weather forecasting less accurate. Is there any thing global warming cannot do?

    “The study How Global Warming Changes the Difficulty of Synoptic Weather Forecasting by Sebastian Scher and Gabriele Messori at the Department of Meteorology, published in Geophysical Research Letters, establishes that our ability to make accurate weather forecasts is affected by the current changes in the global climate.” That is ridiculous.

    Yesterday’s hailstorms in Oklahoma were incredibly well forecast:

    The record “bomb cyclone” ten days ago was well forecast. Two days before:

    The flooding in the Midwest was well forecast.

    The entire field of climate study (it is clearly NOT a science, see: ) no longer seems to have any objectivity. Any evil in the world must be due to global warming.

    Does weather science still have challenges? Absolutely. For example, the accuracy of NWS tornado warnings has actually declined the past decade. This seems to be due to 1) more experienced forecasters retiring and, 2) an emphasis on false alarms that has backfired. But, that has nothing to do with global warming.

    • “Is there any thing global warming cannot do? ”

      Is there any research funding that the words “global warming” cannot secure?

    • I’d like to add something to those well forecast events you mentioned. Whether or not they were well forecast in the past,
      They’ve all happened before.

  3. Isn’t the old saw right for a weekly forecast? Two days of weather, five days of lies? The worst at forecasting, I note, are those entities that have accepted the current claims about carbon dioxide hook, line and sinker. The federal government of Canada’s organisation, Environment Canada, and the Canadian TV networks seem to be in that crowd, as CTV can’t predict fairly accurately more than a day or so in advance.

    • The Expulsive
      Yet we now have Doppler Radar and geosynchronous weather satellites, which we didn’t have 50 years ago. Thus, we now have a synoptic view of the weather, and simple extrapolation should be good for a day or two. Thus, it would seem that the computer weather models add little to the predictive ability of meteorologists. Hurricanes have as many predicted paths as there are models. Yet, we are told that these core models allow us to predict temperatures and precipitation a century into the future. I suspect linear extrapolation of recent trends would do a better job for the long term changes. The reality is that the accuracy of weather computer models appears to be inversely related to the length of time into the future the predictions are made. Why should be expect climate computer models to be any different?

      • So called chaos theory, the mathematics of systems of differential equations, was invented by Edward Lorenz an MIT researcher who was working on mathematical models of the weather back in the 1950s. He discovered that very tiny changes in the initial conditions of the models caused wild differences in their end states. That the disturbance of a butterfly flapping its wings in China could lead to a storm in Texas.

        The so called GCMs suffer from these problems in spades. Their grid representation of the earth is based on boxes 1 degree on a side (about 110 Km). The boxes are big enough to have all kinds of butterflies, or even 747s in them. How about whole thunderstorms. A thunderstorm releases as much energy as a medium sized thermonuclear device. Furthermore there is no data available from most of the boxes. There are very few weather stations in middle of the South Pacific for instance.

        Why any credence is given to the outputs of GCMs is question that can only be answered by psychologists and political scientists.

        • and thunderstorms are a moving source of heat that influences all sorts of weather in its path.
          Many of the equations in the models require boundary values in order to make a sensible equation that can be solved.
          Are the grid boxes allowed to influence each other directly? i.e. passing the thunderstorm along as it moves. Or do they only change boundary conditions.

        • One of my professors at Purdue, John Robert (“Bob”) Osborne, made what I consider to be the best one-sentence rebuke of the “butterfly effect” when he said: “Nature doesn’t differentiate, it integrates.” It was a comment on science’s and engineering’s’ reliance on differential equations for modeling physical phenomena. They are far easier to solve than integral equations, which is why we use them. But integral equations are better representations of reality, and often precede their differential substitutes (the Navier-Stokes equations being a notable example).

          Those of us old enough to have been taught to use an analog computer will recall that problems pretty much had to be in integral form, because there was no way to exclude noise from the circuitry: while analog circuits which could mimic differentiation were possible, they would provide the derivative of both the problem signal plus its noise components. In short, they would produce either unstable or at least inaccurate results.

          Digital computers have even subtler ways of screwing up derivatives, but the theory looks so simple and convincing that most modelers are unaware of all of the pitfalls. There is a body of literature on the Lorenz equations suggesting (convincingly) that the so-called chaotic behavior they exhibit is almost entirely an artifact of numerical solutions. There have been other examples in the history of digital solutions, as well. We just never seem to learn.

        • There are very few weather stations in middle of the South Pacific for instance.

          Try forecasting in the South Pacific when there are only six stations for the whole Southern Pacific-And I didn’t even have satellite pictures!!!! (we were too low on the priority list to have them sent) [I am not nostalgic for those days]

      • Clyde, weather models are much more accurate and reliable than most scientists realize at this point. I recently documented (in detail) model predictions of two major regional weather events, and the model outputs which predicted them as much as 1-week to 9-days in advance.

        You’ll be surprised how brilliantly the weather model performed, see these:

        Monsoon Low over North Queensland

        Cyclone IDAI -> Mozambique

        The best weather models have evolved to a point now where enduring skepticism about them isn’t warranted (on the contrary).

        Climate models however are a waste of time IMHO, due to the inability to generate testable real-world future predictions. They’re clearly not science, they’re simulation curiosities that have been misappropriated toward corrupt political ends and are wasting everyone’s time and money (and that’s understating it).

        • WXcycles
          I grew up in California. Because there are really only two seasons, one characterized by hot, sunny weather, the other by cool, rainy weather, it seemed that the weather forecasts were pretty good. When I was drafted, I lived in Vermont for a couple of years. I immediately was struck by how poor the weather forecasts seemed to be, despite the local wisdom of Summer arriving on July 4th and leaving on July 5th. I wrote the situation off to the mountainous topography and the numerous microclimates. I went back to California and was again amazed at what a good job the weather forecasters did in a Mediterranean Climate. I am now living in Ohio, which is not mountainous, and has the traditional four seasons. I’m struck by the fact that the forecasts seem to be so bad that I’ve gotten to believe that if rain is forecast for two days out, I can probably safely plan a hike or picnic. I’m sure that there is rain somewhere in the state, just as there is always an earthquake somewhere on Earth. But, it is common for me to see a Yahoo weather forecast of rain, while the MS weather is just for cloudiness. So, the issue is that different models are giving completely opposite forecasts with respect to precipitation. I live on a high area and it is not uncommon (especially in the Winter) to observe temperatures 10 deg F warmer than the official forecast for the nearby city of Dayton, which is lower in elevation. I’m probably experiencing inversions.

          It seems that predictions of wind speed and direction are pretty accurate, but I don’t pay enough attention to the details to be sure. That is probably a function of the dense network of meteorological stations, weather balloons, and geosynchronous satellites.

          However, on a day-to-day basis, what I usually want to know is whether or not I will need a coat or an umbrella. Because I don’t expect rapid changes in temperature, I can step out the door, and if it is cold, step back in a grab a coat. The umbrella is a little more problematic. Obviously, if it is raining, I go with the bumbershoot. The tricky part is deciding whether to take it along if it isn’t raining, and have the inconvenience of carrying it when I’m not really going to need it! Then there is the issue of trying to decide whether to water my lawn in late Summer. I don’t want to waste water. So, if the forecast is for rain, I don’t water. But, after several days of rain being forecast, and not arriving, my lawn starts to take on the color of a bale of straw. I’ve lost count of the number of times my lawn has dried up as a result of a conspiracy between the rain clouds and my frugalness.

          To properly analyze the accuracy of precipitation forecasts requires a matrix of historical false positives and false negatives, by area. Has anyone done this?

  4. Models fail to perform in case of slight temperature increase ?

    Climate is defined as the integration of weather, this is a direct confession that the more they heat their models, the less they know what really comes out.


    • I’ll be a bit facetious:
      Significant warming is only evidenced in their Climate Models; it has not been conclusively observed for at least a decade.
      Yet this “virtual” warming is messing up their Climate Models.

      Do I have that right?

      • “Yet this “virtual” warming is messing up their Climate Models. Do I have that right?”

        Yes, you have it right, these scientists are complaining that ficticious heating of the Earth’s atmosphere is messing up their weather forecasts.

        These guys ought to pay attention to a thermometer once in a while because global temperatures have been cooling for the last three years. They are complaining about something that doesn’t exist.

        • Weather forecasting is tough. Always has been. It’s getting better but it’s not perfect.
          This study is ignoring the improvements and blaming the “room to improve” on CAGW.
          Grasping at straws to keep the narrative afloat.

  5. We predict that over the next hundred years, the weather will make weather much harder to predict.

    The Onion could scarcely find a place to add any satire to this.

  6. OK. I fully appreciate the difference in weather and climate.
    I understand noise, Shannon’s maths and theorem, and where and how it is applied.

    Nonetheless, what is being said here is NOT “Our medium-long period data and averages are making our short period models less accurate”

    What is being said is “Our long-period models are making our short term models less accurate”

    Most normal experimenters would go back to the drawing board at this point, to check some assumptions.

    If the article had noted “Current data about the following factors is making it more complex than usual to get our short term models to work accurately over a period of X days”
    So re-run all the models. Rebaseline.
    If they still don’t match reality *your model is wrong* – fix it!

  7. The ongoing climate changes make it increasingly difficult to predict certain aspects of weather
    What this shows is that weather prediction models do not properly describe climate.

    Climate change is not the cause. The cause is the simple fact that weather models are a crude approximation of future weather, where many of the important dynamics are instead approximated by fixed variables.

    In many respects weather models are the equivalent of a GPS navigation system that uses average speed instead of actual speed to calculate position. When the actual speed changes the average speed lags, making the position less accurate.

    The problem us not caused by changing speed (climate). Rather it is caused by using crude approximation to represent dynamic variables.

    • There is nothing wrong with the weather forecasting models. They are better than ever. The new mesoscale models (link above w/r/t yesterday’s hailstorms in Oklahoma) are amazing.

      • Nothing wrong? So you can run a model once, and it will forecast with perfect accuracy? 90% accuracy? 50?

        • Usually you don’t have time to run a weather model twice – unless you want to forecast yesterday’s weather.

          I love

          • As a forecasting meteorologist for almost 40 years, I found this article particularly stupid. The daily forecasts are not derived from climate, but from the latest sampling of the atmosphere by all observational platforms. The physics of meteorology does not change if the climate slowly changes.

            Granted, the short term models get increasingly inaccurate beyond a couple of days, and modelers use the climate averages to help keep the chaos in the system from producing unrealistic 5-10 day forecasts, but good meteorologists are aware of this when making their forecasts.

            Like Mike says, the short term forecasting models have been generally improving over the decades, as the quality of the observations has also improved with the addition of satellite data. There have also been large improvement in the models themselves as well as the computational power that is now available. These technical advances, however, only improve the short-term forecasts, because they do not remove the essential flaw of numerical prediction, namely the fact that errors grow with each iteration of the forecast equations. ‘Better’ equations and better data will never overcome this shortcoming of numerical prediction, but they can and have improved the short-term forecasts.

            Climate change is completely irrelevant to the ability of forecast models to predict short-term weather. Only an academic with little to no forecasting experience would come to the conclusion of the above paper.

  8. Step A: open your bedroom window in the morning and look out, and, just to be safer,
    Step B: consult your local weather radar/satellite data for anything over the horizon approaching.

    • A mate of mine reckons the best weather forecasting resource site is –
      (stick yer head out the f’n window)

  9. Climate science is settled :

    – after having spent billions on climate research, we can positively confirm, without any doubt, that we have no clue, none, zero, zip, nada, neither on what climate nor on what weather is, but we made substantial progress in blatant fear-mongering.

    • A. Glaswegian friend of mine has maintained for at least 60 years that “all weather forecasters are drunks or liars” he has never been one to mince his words or suffer fools lightly, I am now of the belief that he may have been on to something over these years!

  10. Weak solar wind during periods of low solar activity causes a blockade of circulation over the North Pacific and North Atlantic.

  11. There ought to be an annual award for the climate science category of “things that are going to get worse assuming everyone is as dull as the study authors”.

    After all… Given that the warming predicted by climate models is well ahead of observations, there should be ample lead time to evolve and adapt weather forecasting methods to maintain current levels of accuracy.

  12. The Austrian bishops’ conference is the most recent [the third] Catholic institution to say it will divest from fossil fuels. Not refusing to consume conventional energy, mind you, just going to stop investing in non-renewable energy companies. So why is the Catholic church investing in any companies? Shouldn’t their monies be going to the feed the poor and comfort the afflicted in their flock (after paying the monthly bills, legal fees, and maintaining their considerable assets, of course)?

    • “The Flock” now consists of delegates to UN conferences, not the great unwashed who used to drop a shilling into the plate as it was passed around each Sunday at mass.

      Besides, churches used to procure all the high ground to build their edifices upon (great real estate investments!), but now all the smart money is going into high ground where wind turbines can be built with taxpayer subsidy $$$$$$s.

      Divine guidance, doncha know?

  13. Off-topic but too good not to be reported here: Scott Adams’ masterly and devastating deconstruction of the central dogma of Climate “Science”.

    Scott Adams is not a scientist, but he has a far deeper understanding of the scientific method and fundamental logic than any so-called climate scientist.

    • start at 17:12 if you want to get right to it.

      I can’t really decide if he’s sincere about his supposed search for the truth or if he’s doing an elaborate play act. He’s obviously a partisan of Trump who has called AGW a hoax. He throws out statements that the skeptics are “obviously lying to you” and he claims to be convinced by the sophomoric explanations at that he claims to think blow away skeptical arguments. He’s smarter than that, so I think he’s playing a game. Unfortunately I doubt very much that it will persuade anybody when he finishes this charade. Surely there are vanishingly few CAGW believers following him and sitting through his Trump stuff, buying into the idea that he’s got an open mind.

  14. Skipping school every Friday makes all aspects of any forecasting more difficult for future climatologists.

  15. Tiny changes in initial conditions can result in large changes in the future weather. This is the definitive case of where chaos theory is applied. Downpours have small area and small duration in addition to chaotic unpredictability. Computing power limits the grid size of the weather model.

    Norway, Finland and Sweden have large archipelagos: If your terrain is full of small islands creating an accurate model is difficult. Grid cells must be small and observations timely and detailed.

  16. So climate change which is measured through long time changes in the weather now comes right around and affects the weather. Ladies and Gentlemen we have found the only perpetual motion machine on earth. The weather or maybe the climate

    • Rather special circumstances. Two tropical cyclones simultaneously charging straight into a cold front coming up from the south.

      But such is the ‘land of parching drought and flooding rain’.

  17. Global warming ate my homework, so can’t predict downfall (der Untergang).

    On the other hand, how difficult it can be in never ending drought?

  18. So climate change makes a good reason why they get all their seances/predictions wrong…

    No schist!

  19. Is this study report what you call feedback loopy?

    At least they’ve got one thing right: “temperature difference between the North Pole and the equator”. Wow!

  20. Have they programmed in significant warming, and it hasn’t happened?

    Is the weight or volume of precipitation over a large area about the same as it was?
    Are they thinking they should be able to get downpours correct for small areas?
    Are they thinking? Okay, sorry!

    • “Have they programmed in significant warming, and it hasn’t happened?”

      I think that is the problem right there.

      These guys need to update their models because It’s been cooling for three years. If you think it is warming and it is really cooling, then that might throw off your calculations.

  21. Stand facing the true wind and the centre will be between three and five points on your right in the northern hemisphere and on your left in the Southern Hemisphere . Note if your barometer has fallen twice the diurnal variation. Note if the cloudscape is tattered fracto – cu. check the wind speed. You may be in the unnavigable quadrant of a tropical revolving storm. Oh – why not listen to Guam radio?

  22. Do we take it that 3-10 day weather forecasting isn’t settled science but 30 year climate forecasting is?

  23. Seems like the met gang has been having a lot of fun with this post, and rightfully so. Comments seem to have drifted a bit, so I’m going to return to the first paragraph of the report.

    To my mind, I feel it is absolutely correct. I’ve been trying to predict the weather for over 50 years and I swear that trying to predict QPF 3-10 days ahead during the summer is the highest forecast uncertainly around. All the article does is state that will continue far into the future. That finding is so obvious that I can’t believe anyone would spend the time and money “researching” it.

    Summer QPF 3-10 day forecasts are by far the worst of the seasonal 3-10 day QPF’s. Always have been; always will be. (Of course, “always” isn’t such a long time for me.)

  24. Damn climate change. I’m really going to miss those 100% accurate weather reports we all got used to.

  25. Just think what advances in the science and accuracy of weather forecasting might have been made if just a quarter of the cash spent on the political “science” of CAGW hadn’t been wasted?
    They love to invoke our future children.
    How about doing something for our present children now?

  26. The true value of CAGW- the universal excuse. There is no human incompetence that cannot be masked by global warming models.

  27. This doesn’t pass the smell test.

    Lowering the temperature gradient between the poles and the tropics results is less movement of air masses and at lower velocities…and with less mixing (therefore less chaos). With air masses moving more slowly, weather conditions would change more slowly providing for longer weather prediction horizons.

    We see this in microcosm with large “blocking” high pressure systems that can be very large and very uniform in temperature and pressure across its expansive area. Weather predictions can be spot on for weeks ahead WHEN NOTHING IS CHANGING.

    This is the reason the cyclone energy has decreased with recent warming (directly contrary to the predictions of more and stronger cyclones/hurricanes).

    This unending Fake Science “parade” is like watching a never ending nightmare episode of “The Outer Limits”.

  28. Weather forecasting has always been difficul and erratict. It has gotten worse recently as the focus has been on substantiating the effects of ‘ ‘Global Warming/Climate Change’. However, this same ‘Climate Change/Global Warming’ provides a good excuse to explain why the present forecasts are so inaccurate.

  29. You don’t need to read further than the heading.

    What a pile a garbage. I’m getting sick to death of the proliferation these contemptible, ridiculous, useless, inane, bullshit ”studies” These people couldn’t ”study” their way out of a wet paper bag.

  30. So, is climate change make forecasting weather more difficult? Or is incorporating human caused climate change into forecasts making them less accurate? I bet it’s the latter.

  31. Generally the forecast for a couple of days out is all you need. You plan your activities based on what the weather will most likely be understanding that it could change. Now a lot of times when a certain type of pattern develops the forecast can go up to 5 days out and be accurate. Of course, summer forecasts for Florida are “warm and humid with a chance of pop up thunderstorms”. Repeat as necessary.

  32. Unless it’s a bad translation, these guys are in trouble with their title – “How Global Warming Changes the Difficulty of Synoptic Weather Forecasting”. Don’t they know that it is “Climate Change”, not “Global Warming”.

    I don’t see any problems in the future with predicting summer rainfall amounts here in the Southern California coastal plain. A trace here, a trace there. Same old same old.

    I’d prefer it if the predictions were wrong and we got significant rainstorms all summer long.

  33. “There is no such thing as bad weather, only inappropriate clothing”

    Which doesn’t quite explain Her glee in reminding you who’s the boss, when She catches you out.

  34. Climate Change has definitely made one aspect of weather forecasting much poorer.

    All the f’n wind turbines are in the way of the Doppler radar!

    The radar that I use is 70 miles away, and by the time it clears the newish turbines and gets overhead, snow squalls have an easy time getting in underneath. Much worse than it used to be.

    I don’t the details on tornado tracking, but I can’t see how they are not affected.

  35. “… The study How Global Warming Changes the Difficulty of Synoptic Weather Forecasting by Sebastian Scher and Gabriele Messori at the Department of Meteorology, published in Geophysical Research Letters, … ”

    Is Meteorology still part of the Humanities faculty?

    I suspect this is a large part of the reason why these two Meteorologists don’t seem to have any real comprehension of the basic differences in scale between climate change and weather change, or seasonal changes. If they did they’d never have made such a scientifically unschooled and false claim.

    ” … The ongoing climate changes make it increasingly difficult to predict certain aspects of weather, according to a new study from Stockholm University. The study, focusing on weather forecasts in the northern hemisphere spanning 3-10 days ahead … ”

    They’re simply too naive, presuming and ignorant to even feel professionally embarrassed by saying something as that. Meteorologists should stick to meteorology, because these two know nothing about what constitutes a real climate change.

    Hint: it doesn’t appear within a model, and it also doesn’t resolve within a human life time, or meteorology career.

  36. “Claim: Climate changes make some aspects of weather forecasting increasingly difficult.”

    LOL…. What? Considering the history of weather forecasting! This is a laughable statement. Most people planning a picnic on a Sunday who were looking at Friday’s forecast of sunny skies and mild temperatures for the weekend, usually packed an umbrella and a jacket.

  37. Given that weather forecasting has always been hit and miss over more than 72 hours beyond, it will be warming in summer that in winter, this is in reality very old news indeed. Oddly this difficulty has never stopped them claiming certainty over 50 or 100 years for temperature levels to two decimals places, despite all the problems that exist in the theory , the poor practice of the professional working in the area and the ‘better than nothing ‘ reality of the data collection system which includes ‘magic tree rings ‘ .

  38. So who knew forecasting is very hard particularly the future?
    And how much did it cost for this gem?

    James Bull

  39. Claim: Climate changes make some aspects of weather forecasting increasingly difficult

    Apparently this is correct as long-range & even relatively short-range forecasts have become almost universally too warm anymore. Of course those forecasts use no on-the-spot human judgement because they’re just straight from the computer models.

  40. Translation: They can’t tell the difference between “rain this afternoon” and “rain for 5 days.”

  41. Beyond ridiculous. And the abstract quoting the diminishing polar/equator gradient does not help their credibility.

  42. It is difficult when the weather does not comply with global warming theory. Maybe they should try the old fashion way of observation and dump the theory of last chance when it comes to predicting 10 day weather.

Comments are closed.