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Fifty Years Later 
 

Anders Persson 
Swedish Meteorological and Hydrological Institute (SMHI) 

Stockholm, Sweden 
 
In 1974 I had the privilege of meeting and talking to Jacob (Jack) Bjerknes in Bergen, 
Norway, a city immortalized in the history of meteorology thanks to the "school" that 
Jack and his father founded in 1917.  We were in Bergen for the 9th Nordic 
Meteorologist Meeting (NMM9), held every two years in one of the Scandinavian nations 
on a rotating basis. This was during a rare spell of dry and sunny weather, unusual for 
this part of rainy western Norway, and the hosts had invited two of their most legendary 
meteorologists: Bjerknes, who had come all the way from Los Angeles and Sverre 
Petterssen who was supposed to come from London. But these were the times of the 
Vietnam War and the Watergate scandal, and Sverre Petterssen had renounced his U.S. 
citizenship in an angry letter to the White House (Petterssen, 2001). Stateless and thus 
without any passport, he could therefore not leave the UK. 

Jack’s youthful memories 
Petterssen’s absence was to some extent compensated for by Erik Palmén from 

Finland who regularly attended the NMMs (fig. 2.1). His friendship with Jack dated back 
to the period between the world wars when, through their theoretical and practical works, 
they engaged in scholarly combat with their German and Austrian doubters and 
opponents (Friedman, 1989, p. 246; Bergeron, 1959, p. 462; Haurwitz and Haurwitz, 
1939, p. 53 ff). 

I had hoped to learn more about this from Jack when we sat down in the park 
outside the Geophysical Institute. But recollections of his youth were freshest in Jack's 
memory. Born in Stockholm, with the first nine years of his childhood there, and then 
with almost half his life in the United States, he didn’t feel very "Norwegian": “Jeg føler 
meg mere svensk enn norsk,” he let slip. However, when the import of what he had said 
hit him, he corrected himself quickly: “men mest av alt nordisk!”1 

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
1 ”I feel more Swedish than Norwegian – but most of all Nordic!” 



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Fig. 2.1. Eric Palmén and Jack Bjerknes inspecting weather charts at NMM9 in 1974. Photo taken 

by Anders Persson. 

 
Jack’s lecture on climate change 

The NMMs featured numerous lectures on mixed meteorological topics. Jack 
Bjerknes chose to speak on his latest research. While all young career minded 
meteorologists used to fill the blackboard with mathematical equations, Jack just wrote A 
+ B and drew a trapezoid. The trapezoid symbolized the Pacific and A + B the warm and 
cool surface water oscillations between the El Niño and La Niña phases, the more A, the 
less B etc. 

Now, 40 years later, it is easy to see that we had listened to a speech of historical 
significance in the meteorological-oceanographic sciences. At that time, within the broad 
meteorological community the “climate” was something you worked out in 30–year 
periods and which was determined by the variations in the Earth's path and axis tilt, 
perhaps also volcanic eruptions and human emissions after a nuclear war. With the El 
Niño (Southern Oscillation) attention was drawn to the atmospheric internal variability. 

In 1974 the oceanographic measurements were still rudimentary, to any extent 
with only surface water temperatures. Jack Bjerknes and his oceanographer colleagues at 
that time would have felt like children on Christmas Eve with a very generous Santa 



	
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Claus if they had had access to today's networks of both surface and deep-based ocean 
measurements. 

The importance of satellites 
One day we visited the weather ship Polar Front II or “Mike” lying in Bergen 

harbour for overhaul. Its sister ship Polar Front I was on duty out in the Norwegian Sea. 
While expressing a high opinion of the weather satellite's future importance, Jack felt in 
1964 that it would require a global network of weather ships with aerological equipment 
to reap the benefits of modern numerical forecasting.    

For the next two decades meteorologists would convert satellite radiance 
measurements into artificial radiosonde observations (SATEMs) which were then 
assimilated by the numerical forecast systems analysis in the same way as usual 
radiosonde observations . This was still the situation when I was employed at ECMWF in 
1991. However, since the creation of these SATEMs involved interaction with another 
NWP system, it was seen as “incestuous,” and work had already started on the 4-
dimensional variational analysis system (4DVAR) that would revolutionize the NWP and 
help to consolidate ECMWF as the leading NWP centre. 

4DVAR 
The idea of variational analysis had originated with Soviet researchers but had 

been taken over and pursued by French meteorologists Olivier Talagrand, Phillippe 
Courtier, Florance Rabier, Jean-Noël Thepaut and others. The first innovation with 
4DVAR was that the satellite radiance data could be assimilated much more smoothly if 
the model's "first guess" figured out what radiances the satellites "ought to" observe. 
Through sophisticated algorithms the differences were used to correct the analysed 
temperatures and humidities to make the emitted radiances as close as possible to the 
observed ones. The second innovation with 4DVAR was its dynamic consistency. In the 
same way as any forecast meteorologist who analyzes an 18 UTC map of the North 
Atlantic with the scattered ship observations is keen to look back on the earlier maps at 
15 UTC, 12 UTC, and maybe 09 UTC to make a reassessment of the analyzes and 
observations in light of the later 18 UTC data, the mathematical algorithm in 4DVAR 
went back and forth over a 6-hour time window to make observations affect the analyses 
in a dynamically consistent way.  

It was intriguing to witness, how a single moisture observation thereby could 
change the wind and geopotential fields.  These changes also prevented the humidity data 
from being wiped out because of physical-dynamic imbalances. Today's scientists trying 
to assimilate moisture information from the radar echoes face the same problem: without 
modification of the wind, the important moisture information is smoothed out in a few 
hours. 

The development of 4DVAR was very much a French affair and benefited from 
an almost endless stream of young female scientists from Météo France, including 
Florence Rabier, Mathilde Hervour, and Elisabeth Gérard, who had been recruited by 
Phillipe Courtier.  I managed to break into this coterie when, once during one of our 
missions together, we discussed my section’s forecast error tracking using “group 
velocity thinking”. Back at ECMWF Courtier organized a project “to do with 



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mathematics what Anders is doing with his eyes.” In very simple words, it meant running 
the 4DVAR backwards in time (Rabier et al., 1993; Persson 1999, 2000). The 4DVAR 
technique has also found its use in climate research by enabling scientists to analyze the 
3-dimensional structure of the atmosphere back into the 19th century, maybe into the 
1780s, from only surface observations.  
The future of weather forecasters 

At the NMM9 in 1974 all this progress was not even dreamt of when we gathered 
one afternoon to discuss the future of human weather forecasters in the light of computer 
forecasts. Meteorologists were divided into two competing "camps": one claiming that in 
"5-10 years" there would be no need for any forecasters, another claiming that no 
computer could ever replace an experienced weather forecaster. In 1964, Jack Bjerknes 
had not seen any conflict between forecasters and NWP, and that was also the opinion 
both Sigbiørn Grønaas and I expressed in the 1974 debate.  

When I became more and more engaged at ECMWF in the 1980s, it turned out 
that there was a need for meteorologists who stood with one foot in both "camps." I was 
drawn into the information and education activities, with a focus on how best to use the 
ECMWF medium-term forecasts.  

I must admit that it was not totally clear what should be taught. Much of 
forecasting was intuitive and based on experience. If you wanted to learn to write poetry 
or cook Italian food, there was a plethora of books, but not on how to do weather 
forecasting using NWP. The “User guide to ECMWF forecast products” (2011), which I 
became in charge of, tried to remedy this want. I was not quite satisfied with it at the time, 
but there was nothing better. 
The limits of predictability 

In 1974 what would become ECMWF was taking shape.2 At the NMM9 we 
learned that Norway had decided to stay cautious, among other reasons because they 
doubted that 10-day forecasts were ever possible. At this time the useful predictability 
was 4-5 days, and there was great uncertainty about how much it could be extended. 

The question has been raised (Elsner and Honoré, 1992) why it took so long for 
Edward Lorenz 's classic predictability papers (Lorenz, 1963; 1969) to have influence? In 
1972 I made a study of the predictability literature and found that in the 1960s he had 
been considered too pessimistic at a time when overly optimistic predictability studies 
pointed at 20+ days predictability. This was, however, shown by Döös (1969, p.53) to be 
due to misinterpreted verification statistics. But leading Scandinavian scientists still told 
me that there was an "energy gap" between synoptic and subsynoptic waves that would 
confine the forecast errors to the latter. On the other hand, studies had shown that the lack 
of observations over the North Pacific Ocean would set a limit of 5-6 days predictability 
over Europe. All those concerns lingered into the 1990s when they came to naught when 
the use of satellite data through 4DVAR made us almost independent of surface 
observations over the North Pacific and other oceans. The predictability of the global 

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
2 http://www.ecmwf.int/about/history/. 



	
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forecasts is now considered to be 8-9 days and perhaps the “20 days optimists” from the 
1960s will be right one day, albeit for the wrong reason.  

From this perspective, ECMWF and other NWP centres should be counted in the 
same high scientific class as CERN and the Hubble Space Telescope. While the former 
penetrates into the smallest components of matter and energy and the latter explores the 
extent of the universe, NWP raises the fundamental question of how far we can see into 
the future. Is "Laplace’s Demon" possible, an existence mastering all natural laws and 
knowing the initial conditions who can calculate everything that will happen or has 
happened?  This challenge was a great inspiration to the father of NWP, Vilhelm 
Bjerknes and has remained so for many NWP modelers (see Bergeron, 1959, pp. 440-41) 

But from a down-to-earth practical point of view: the details of even the most 
high-resolution weather forecasts are inaccurate within a day or so. The “jumpiness” of 
NWP is an additional source of annoyance, since the next run may come up with a 
completely different development and thereby appear to disavow the earlier forecast. 

In 1986 I attended a meeting at ECMWF where a group of Dutch meteorologists 
emphatically pointed out that any forecast is pretty useless unless there is a way to tell 
how likely it is (Tennekes et al., 1986). Inspired by Americans visionaries (Chuck Leith, 
E S Epstein, Phil Thompson) this initiated research first in "forecast forecast skill" and 
then, when computer capacity allowed, in ensemble technique (Lewis, 2005). This was 
the second major meteorological revolution in the 1990s I had the privilege to take part in. 

An often-overlooked asset at ECMWF, at that time lacking in many other 
research institutions, was their excellent restaurant! It encouraged cross-fertilizing 
contacts across sectional and departmental boundaries. It gave young scientists 
opportunities to meet more established colleagues and visitors. You might one day find 
yourself discussing group velocity with Brian Hoskins in the lunch queue, next day 
follow Eugenia Kalnay and Tim Palmer arguing over perturbations techniques over the 
roast beef and at the end of the week, over a cup of coffee, listen to Ed Lorenz’s 
recollections when he was a weather forecaster in the Pacific during WWII. 

Ensemble forecasts 
While the work on 4DVAR tried to reduce the analysis errors, the work with 

ensemble system was almost the opposite. A large number (first 32 later 50) of 
alternative analyses, perturbed within analysis uncertainty, were created. If 10-day 
forecasts, run from these modified analyses, were in general in agreement with each other, 
we could be pretty sure of the prognosis irrespective of any faulty or misinterpreted 
observations upstream. In case they differed much, we could at least get an idea of what 
would not happen, and probability estimates for possible developments. 

This statistical approach to weather forecasting faced some difficulties in finding 
support among meteorologists in both "camps." In spite of their disagreements, they were 
united by their common classical deterministic Newtonian training. Statistics, "the 
science of uncertainty" was at best seen as a kind of perfume: it's good that it exists, but it 
is a pity that it needs to be used. To express uncertainty in any form was seen as worst as 
“cowardliness”, at best as a way to conveniently cover your back. The realisation that in a 
world with non-perfect forecasts the uncertainty information had a positive value, 



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increased the usefulness of the forecasts, still had a long way to go. This became the main 
theme in the 2011 edition of the “User Guide to ECMWF Forecast Products”, the one I 
am most satisfied with. 
Statistics in meteorology 

If the haunting spectre in 1964 for many in the meteorological community was the 
computer, it today seems to be the growing influence of statistical thinking that 
challenges the classic deterministic thinking. But statistical know-how is needed in our 
age of “Big Data” (Mayer-Schönberger and Cukier, 2013) 

The weather forecaster stands in a flow, or rather “overflow” of information—as 
do stockbrokers, politicians, military—and just like them acts as an “intuitive statistician” 
(Kahneman, 2011). They have to make quick decisions with conflicting indications from 
various models, the sudden appearance of new information from radar screens or 
oceanographic buoys. However, the assessment of uncertainty is complicated by a human 
tendency to be overconfident; to rather look for arguments that support an idea than those 
that contradict it. Underestimation of randomness may fool the forecasters to see 
systematic behaviors in the models where there are none. Then there is the problem of 
how to present forecast uncertainty in a form that is understood and - not least, gives a 
fair chance to make the right decision. 

With the increasing emphasis on extreme or "high impact" weather resistance 
against probability forecasts is slowly giving way. Even the most hardcore determinists 
realize they may have to shelve their planned mountaineering even if the probability of 
snow and storm gusts is less than 100%. In a New Year's reflection in 2005 the then 
SMHI's Director Maria Ågren held the view that also the climate debate needs to be more 
probabilistic: probabilities of severe climate deterioration need not be 100% or even 95% 
to justify action. 

I think Jack Bjerknes would be pleased to see that, despite prophecies to the 
contrary, the weather forecasters are still with us and perhaps there have never been so 
many around as today, not least in the private companies. Maybe they remain, not 
"despite" the computer, but "thanks” to the computer. Thanks to the high quality of the 
weather forecasts, people can now begin to take them seriously into account. But to do 
that most efficiently they need to know more about their uncertainties and possible 
extremes. Here lie the challenges for the future. 

 
References 
Bergeron, T., 1959: Methods in Scientific Weather Analysis and Forecasting. In An 

Outline in the History of Idea and Hints at a Program, in The Atmosphere and The 
Sea in Motion, Scientific Contributions to The Rossby Memorial Volume, Ed. B. 
Bolin, pp. 440-474. Stockholm,	
   Rockefeller	
   Institute	
   Press	
   and	
   Oxford	
  
University	
  Press. 

Döös, B.R., 1971: The Status and Outlook of Numerical Weather Prediction, Zeitschrift f. 
Meteorologie 22:1-2, 46-53. 



	
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ECMWF Seminar Proceedings 6-10 September 1999, pp. 123-38, 
http://www.ecmwf.int/publications/library/do/references/show?id=85676 

Elsner, J.B. and J.C. Honoré, 1994: Ignoring Chaos, Bull. Am. Met. Soc. 75:10, 1846-47. 
Friedman, R.M., 1989: Appropriating the Weather, Vilhelm Bjerknes and the 

Construction of Modern Meteorology, Ithaca, NY, Cornell Univ. Press, 251 pp. 
Haurwitz B. and Haurwitz, E., 1939: Pressure and Temperature Variations in the Free 

Atmosphere over Boston, Harvard Meteorological Studies, 3, Cambridge, Mass., 
Harvard University Press; London, H. Milford, Oxford University Press, 74 pp. 

Kahneman, D., 2011: Thinking, fast and slow. Allen Lane, Penguin Books, 499 pp. 
Lewis, J., 2004: Roots of Ensemble Forecasting, Mon. Wea. Rev. 133:7, 1865-85. 

Lorenz, E., 1963: Deterministic nonperiodic flow, J. Atm. Sci. 20, 130-41. 
_____.. 1969: The predictability of a flow that posses many scales of motion, Tellus 21, 

289-307. 
Mayer-Schönberger, V. and K. Cukier, 2013: Big Data, A Revolution That Will 

Transform How We Live, Work and Think, John Murray, 242 pp. 
Persson, A. 1999: Monitoring the ECMWF forecast system by dynamical methods, pp. 

150-153. 13th conference on Numerical Weather Prediction, Denver, Colorado, 
13-17 September 1999, Am. Met. Soc., Boston. 

_____. 2011: User Guide to ECMWF forecast products, available at 
http://www.ecmwf.int/products/forecasts/guide/user_guide.pdf 

Petterssen, S,. 2001: Weathering the Storm: Sverre Petterssen, the D-Day Forecast, and 
the Rise of Modern Meteorology, J.R. Fleming, ed. Am. Met. Soc. Boston, 329 
pp. 

Rabier, F, P. Courtier, M. Hervou, B. Strauss and A. Persson, 1993: Sensitivity to 
forecast error to initial conditions using the adjoint model. ECMWF Tech. Memo 
197,  http://www.ecmwf.int/publications/library/do/references/show?id=83728 

Tennekes, H, A.P. Baede and J.D.Opsteegh, 1986: Forecasting forecast skill, Workshop 
on Predictability in the Medium and Extended Range 17-19 March 1986, 
available at http://www.ecmwf.int/publications/library/do/references/list/16234 

 

 
Anders Persson (b.1944) chose a career in meteorology in 1964, the year of Bjerknes’s 
essay, “Half a century of change in the meteorological scene,” in the mistaken belief that 
meteorology was a simpler science than quantum mechanics or relativity theory. Starting 
as a weather forecaster at SMHI and then as a senior scientist at ECMWF and the British 
Met Office, he has, at close range, followed the spectacular development of numerical 
weather prediction (NWP), one of science’s great success stories. 


