RealClimate

Climate science from climate scientists...

You are here: Home / Archives for rasmus

About Rasmus Benestad

I am a senior scientist working at the Norwegian Meteorological Institute with a background from physics. My scientific career started with a degree in Physics with Electronics at UMIST in Manchester (UK), cloud micro-physics at New Mexico Tech (USA), and ocean physics at Atmospheric Oceanic and Planetary Physics (AOPP) at Oxford University (UK). Since then, I have also got heavily involved in the field of statistics, thanks to exciting collaborations with several statisticians.

My primary focus at the Norwegian Meteorological Institute has been towards climate change adaptation, empirical-statistical downscaling and anthropogenic climate change, but I have also worked on problems relating to natural climate variations connected to changes in the sun. I have authored two text books on these topics: Solar Activity and Earth's climate (Praxis/Springer) and Empirical-Statistical Downscaling (World Scientific Publishers).

My experience from the climate science community includes several roles: a contributing author on two past IPCC assessment reports, a person of contact (POC) for World Climate Research Programme's (WCRP) CORDEX project, a coordinating lead author on Arctic Monitoring and Assessment Programme's (AMAP) report Adapting Actions in a Changing Arctic (AACA, 2017), a councilor for the European Meteorological society (EMS), a member of the EMS communication and media committee, and part of the advisory board for Oxford Research Encyclopedia on climate. I also chair the professional network within the Norwegian trade union for engineer and natural scientists Tekna Klima, dealing with a diverse range of climate solutions.

Climate Adaptation Summit 2021

by

The first ever Climate Adaptation Summit (#adaptationsummit) that I have heard about took place last week, on January 25-26. I think such a summit was a step in the right direction. It was adapted to the Covid-19 situation and therefore an online virtual summit streamed on YouTube. 

I watched a few of the streamed sessions, and it struck me that climate change adaptation seems to be a fairly new concept to many leaders. It were sometimes mix-ups with mitigation during the high-level talks. Mitigation and adaptation are both important and sometimes they overlap, so mix-ups are understandable. 

One important point addressed during the summit was of course financing climate change adaptation, which is promising. Financing is clearly needed for climate change adaptation. To ensure progress and avoid lofty visions without results on the ground, there may also be a need for tangible results and to show examples and demonstrations. One specific type discussed at the summit was “Early warning systems” which play an important role.

But it was not crystal clear what was meant by the concept “early warning systems”. My interpretation is that it involves something on par with weather forecasts which would imply that they are more about weather than climate. This is of course important too. Probably the first priority in many places. 

But early warning systems, the way I understand them, don’t provide information about climate risks on longer timescales. Weather and climate – short and long timescales – are of course connected but nevertheless different (“climate” can be viewed as weather statistics). Other examples of climate adaptation can be found in a recent Eos article on food security in Africa. I think it is important to mention maladaptation and avoid long-term problems connected to short-term fixes. Resilience is a keyword. 

As with many other summits, I felt that the scientists’ voice was largely missing. There seems to be a gap between high-level politics and science. I think we need a better dialogue between the leaders and climate scientists partly to help distinguish between different and difficult concepts. But the main reason is that we need to know what we must adapt to. We need to know the situation: the state of the climate and how it is changing. This knowledge is not readily downloadable from the Internet.

There are key questions that should involve scientists: What is needed for proper climate change adaptation? And what are the challenges in terms of meeting our objectives? What do we know about future risks? In addition, biodiversity, nature conservation, cultural, social and economic aspects are important. 

Data is crucial, but is often unavailable because of lack of sharing and lack of openness. Often due to lacking finance. Information about the regional climate change must be distilled from large volumes of data, and we need to ask what information is useful and how it can be used in the best possible way.

The required analysis is often carried out in climate services and often includes downscaling. It involves tools, methods and understanding that are still evolving with regards to these topics. This fact wasn’t explained clearly during the summit in the sessions I watched. I think it would be useful with a presentation of the state of climate science relevant for climate change adaptation at a high level in the summit. Perhaps science should get an equal amount of attention as the NGOs and the businesses. 

Much of the latest research relevant to the climate adaptation summit is coordinated within the World Climate Research Programme (WRCP) which also is setting a new focus on regional information for society (“RifS”). Furthermore, there is considerable scientific experience on adaptation from the Arctic with the fastest climate change on Earth, such as the Adaptive Actions in a Changing Arctic (AACA) report for the Arctic Council. 

Climate adaptation involves many communities and disciplines (e.g. weather forecasting, climate services, regional climate modelling, “distillation“, disaster risk reduction) which I think aren’t well coordinated at the moment. One message from the summit was “Let’s work together” which I think implies a better coordination of the different disciplines and communities.

The number of tropical cyclones in the North Atlantic

by


2020 has been an unusual and challenging year in many ways. One was the record-breaking number of named tropical cyclones in the North Atlantic (and the Carribean Sea). There has been 30 named North Atlantic tropical cyclones in 2020, beating the previous record of 28 from 2005 by two.

A natural question then is whether we can expect this high number in the future or if the number of tropical storms will continue to increase. A high number of such events is equivalent to a high frequency of tropical cyclones.

But we should expect fewer tropical cyclones generally in a warmer world according to the IPCC “SREX” report from 2012, and those that form may become even more powerful than the ones that we have observed to date:

There is generally low confidence in projections of changes in extreme winds because of the relatively few studies of projected extreme winds, and shortcomings in the simulation of these events. An exception is mean tropical cyclone maximum wind speed, which is likely to increase, although increases may not occur in all ocean basins. It is likely that the global frequency of tropical cyclones will either decrease or remain essentially unchanged…

So how does this conclusion relate to the number of tropical cyclones in the North Atlantic with a new record this season? One reason to look in more detail at the North Atlantic is because its observational record is believed to be more complete and more reliable than for other regions around the world.

The observational record may also suggest that the number of tropical cyclones in the North Atlantic has increased slowly over the 50 years in addition to year-to-year fluctuations around this trend (black symbols in Fig 1).

We know that the number of cyclones is sensitive to the time of the year (hence, hurricane seasons), phenomena such as El Niño Southern Oscillation (ENSO) and the Madden Julian Oscillation (MJO), and geography (the ocean basin shape and the latitude). We also know that the sea surface needs to be warmer than 26.5°C for them to form.

The role of sea surface temperature is indeed an important factor, and from physical reasoning, one would think that the number of tropical cyclones depends on the area of warm sea surface A (sea surface temperature exceeding 26.5°C).

One explanation for why the area is a key factor may be that the probability of finding favourable conditions with right ‘seed’ for organised convection (e.g. easterly waves) and no wind shear increases when there is a greater region with sufficient sea surface temperatures.

The area of warm sea surface is mentioned in the IPCC SREX that dismisses the expectation that an increase in the area extent of the region of 26°C sea surface temperature should lead to increases in tropical cyclone frequency. Specifically it says that there is

a growing body of evidence that the minimum SST [sea surface temperature] threshold for tropical cyclogenesis increases at about the same rate as the SST increase due solely to greenhouse gas forcing.

On the other hand, there has also been some indication that the number of tropical cyclones does seem to be proportional to the area to the power of 5: n \propto A^5 (Benestad, 2008). When this relationship is extended to recent years, as shown with the green and blue curves in Fig 1, we see an increase that this crude estimate more or less follows the observed number of evens.

Global warming implies a greater area with sea surface exceeding the threshold of 26.5°C for tropical cyclone genesis. Also, the nonlinear dependency to A implies few events and little trend as long as A is below a critical size. The combination of a nonlinear relationship and a critical threshold area could explain why it is difficult to detect a trend in the historical data.

There is some good news in that A is limited by the geometry of the ocean basin. Nevertheless, a potential nonlinear connection between the number of tropical cyclones and A is a concern. If this cannot be falsified, then the tropical cyclones represent a more potent danger than anticipated by the IPCC SREX conclusions. So let’s hope that somebody is able to show that the analysis presented in (Benestad, 2008) is wrong.

Fig 1. Observed (black symbols) and estimated (green and blue curves) number of named tropical cyclones in the North Atlantic and the Caribbean Sea after (Benestad, 2008). Source: “demo(tropicalcyclones)”.

References

  1. R.E. Benestad, "On tropical cyclone frequency and the warm pool area", Natural Hazards and Earth System Sciences, vol. 9, pp. 635-645, 2009. http://dx.doi.org/10.5194/nhess-9-635-2009

Thinking, small and big

by

The point that climate downscaling must pay attention to the law of small numbers is no joke.

The World Climate Research Programme (WCRP) will become a ‘new’ WCRP with a “soft launch” in 2021. This is quite a big story since it coordinates much of the research and the substance on which the Intergovernmental Panel on Climate Change (IPCC) builds.  

 

Until now, the COordinated Regional Downscaling EXperiment (CORDEX) has been a major project sponsored by the WRCP. CORDEX has involved regional modelling and downscaling with a focus on the models and methods rather than providing climate services. In its new form, the activities that used to be carried out within CORDEX will belong to the WCRP community called ‘Regional information for society’ (RifS). This implies a slight shift in emphasis.

 

With this change, the WCRP signals a desire for the regional modelling results to become more useful and relevant for decision-makers. The change will also introduce a set of new requirements, and hence the law of small numbers.

 

The law of small numbers is described in Daniel Kahneman’s book ‘Thinking, fast and slow‘ and is a condition that can be explained by statistical theory. It says that you are likely to draw a misleading conclusion if your sample is small.  

 

I’m no statistician, but a physicist who experienced a “statistical revelation” about a decade ago. Physics-based disciplines, such as meteorology, often approach a problem from a different angle to the statisticians, and there are often some gaps in the understanding and appreciation between the two communities.

 

A physicist would say that if we know one side of an equation, then we also know the other side. The statistician, on the other hand, would use data to prove there is an equation in the first place.

 

One of the key pillars of statistics is that we have a random sample that represents what we want to study. We have no such statistical samples for future climate outlooks, but we do have ensembles of simulations representing future projections.

 

We also have to keep in mind that regional climate behaves differently to global climate. There are pronounced stochastic variations on regional and decadal scales that may swamp the long-term trends due to greenhouse gases (Deser et al., 2012). These variations are subdued on a global scale since opposite variations over different regions tend to cancel each other.

 

CORDEX has in the past produced ensembles that can be considered as small, and Mezghani et al., (2019) demonstrated that the Euro-CORDEX ensemble is affected by the law of small numbers.

Even if you have a perfect global climate model and perfect downscaling, you risk getting misleading results with a small ensemble, thanks to the law of small numbers. The regional variations are non-deterministic due to the chaotic nature of the atmospheric circulation.

 

My take-home-message is that there is a need for sufficiently large ensembles of downscaled results. Furthermore, it is the number of different simulations with global climate models that is key since they provide boundary conditions for the downscaling.

 

Hence, there is a need for a strong and continued coordination between the downscaling groups so that more scientists contribute to building such ensembles.

 

Also, while CORDEX has been strong on regional climate modelling, the new RifS community needs additional new expertise. Perhaps a stronger presence of statisticians is a good thing. And while the downscaled results from large ensembles can provide a basis for a risk analysis, there is also another way to provide regional information for society: stress-testing.

References

  1. C. Deser, R. Knutti, S. Solomon, and A.S. Phillips, "Communication of the role of natural variability in future North American climate", Nature Climate Change, vol. 2, pp. 775-779, 2012. http://dx.doi.org/10.1038/nclimate1562
  2. A. Mezghani, A. Dobler, R. Benestad, J.E. Haugen, K.M. Parding, M. Piniewski, and Z.W. Kundzewicz, "Subsampling Impact on the Climate Change Signal over Poland Based on Simulations from Statistical and Dynamical Downscaling", Journal of Applied Meteorology and Climatology, vol. 58, pp. 1061-1078, 2019. http://dx.doi.org/10.1175/JAMC-D-18-0179.1

How to spot “alternative scientists”.

by

Recently, a so-called “white coat summit” gave me a sense of dejavu. It was held by a group that calls itself ‘America’s Frontline Doctors’ (AFD) that consisted of about a dozen people wearing white coats to the effect of achieving an appearance of being experts on medical matters.

 

The AFD apparently wanted to address a “massive disinformation campaign” (what irony) and counter the medical advice from real health experts. This move has a similar counterpart in climate science, where some individuals also have claimed to be experts and dismissed well-established scientific facts, eg. that emissions of CO2 from the use of fossil fuels results in global warming.

 

Climate science is not the only discipline where we see confusion sown by a small number of “renegades”. A few white-coated scholars have disputed the well-established danger of tobacco. We see similar attitudes among the “Intelligent Design” community and the so-called “anti-vaxxers”.

 

Statistically speaking, we should not be surprised by a few contrarians who have an exceptional opinion within a large scientific community. It is to be expected from a statistical point of view where there is a range of opinions, so there should be little reason to make a big deal out it.

 

On the other hand, there are some fascinating stories to be told. Sometimes there are individuals who can be described as “crackpots” and “quakesalvers” (e.g. a scholar believing in dowsing rods among the climate renegades and some within the AFD who talk about demons). Hollywood has even realized that some scientists may be mad, which has given us the familiar term “mad scientist”. But all “renegades” may of course not necessarily be mad.

 

Nevertheless, according to Snopes, the background of the individuals of the AFD is rather colourful. And there is nothing in the background provided about them that gave me any confidence in their judgement. On the contrary.

 

A sign that should trigger a big warning is that Snopes found it difficult to see who the AFD really are or where their conclusions really come from. The transparency is lacking and their story is murky. Especially so if the results have not been published through renowned peer-reviewed scientific journals. This is something we have seen time and again with climate change contrarians.

 

Any claim would be more convincing if colleagues independently are able to replicate the work and get the same results (without finding anything wrong with the process). This would require transparency and openness.

 

Another sign that should make you skeptical is if the claims have a dogmatic character. The AFD address is all dogma. This is also typical among the science deniers.

 

It’s also typical that the extreme fringes cannot falsify the established science and therefore move on to conspiracy theories. In the case of AFD, it is the alleged “massive disinformation campaign”.

 

Should we take such fringe views seriously? This type of “infodemics” seems to become a growing problem as described in a feature article in Physics World July 2020: ‘Fighting flat-Earth Theory’. The term “infodemic” reflects the fact that false information is just as contagious as an epidemic. Imposters dressed in white coats peddling false information can cause harm if people take them seriously.

 

The damage caused by erroneous information and conspiracy theories is discussed in the HBO documentary ‘After truth’, and the wildest claims can spread like a rampant disease as shown in that film.

We have witnessed how misinformation and lack of trust of true medical sciences have caused bad situations in some countries, while in others (eg. New Zealand, Canada, and some Nordic countries) the pandemic has been kept under control because the general public in general has followed the scientific health advice.

 

There is a common denominator when it comes to the AFD, anti-vaxxers, flat-earthers, “intelligent design”, chem-trail evangelists and those dismissing climate science. I think it may be useful to join forces within the broader scientific community to help the general public understand the real issues. This effort should also be on more general terms. People have a right to reliable and truthful information. Everybody should understand that anyone who spreads bullshit or lies also shows you a great deal of disrespect. The same goes for platforms spreading disinformation.

 

So what can we do to make people understand how science works and enhance the general science literacy? Is it better to teach people how to spot these “alternative scientists” (the term is inspired by “alternative facts”), conspiracy theories, and falsehoods, if we show a range of examples from different disciplines? We can probably learn from each others. There seems to be a lesson to be learned from the pandemic.

‘2040’

by

After an absurd period with a real-life gloomy corona pandemic, lock-down and unrest, it was quite refreshing to see visions for a sustainable future in a new documentary ‘2040‘ (link to trailer). Its message, through the voice of Damon Gameau, is about hope and is based on rational thinking.


The video takes us to twenty years fast-forward to an imagined future. It makes good use of effects that communicate. For instance, Damon Gameau speaks with children about green and sustainable solutions and then makes the time travel to show what such a future may look like when climate change has stopped.


The documentary also makes use of some cool effects to demonstrate how things work. But it is mostly about a positive message on solutions rather than emphasising climate science and harmful consequences of climate change.


There is an interesting timing with the release of ‘2040’, and hopefully it will contribute to discussions about new solutions and how we can make use of both technology and new behaviour to improve our lives and the health of the planet. This is something that is already being discussed in Europe.


I thought the documentary made some interesting points about energy production, how to make agriculture more sustainable through mixed crops and good soil health, and how to use ocean resources. Another important point is the importance of empowering girls and women. However, I’m not in the position to say how successful the suggested solutions would be. I guess we may know answers in 2040.

Regional climate modeling and some common omissions

by

There is a growing need for local climate information in order to update our understanding of risks connected to the changing weather and prepare for new challenges. This need has been an important motivation behind the World Meteorological Organisation’s (WMO) Global Framework for Climate Services (GFCS).

There has also been a lot of work carried out to meet these needs over time, but I’m not convinced that people always get the whole story.  

[Read more…] about Regional climate modeling and some common omissions

Unbelievably, this is no April’s fool joke

by

Last week, a colleague shared a tweet with a link to a very unusual paper. I first thought it must be a joke, but then realised that since it was the last days in March when I read it, it could not be an April’s fool joke. It seems to be a serious paper.

So I thought it would be perfect to share the reference McCarthy et al. (2020) today. The paper has a few useful take-home messages, such as the C.R.A.P. framework.

Update: here is a presentation slide deck to accompany the paper. 

References

  1. I.P. McCarthy, D. Hannah, L.F. Pitt, and J.M. McCarthy, "Confronting indifference toward truth: Dealing with workplace bullshit", Business Horizons, vol. 63, pp. 253-263, 2020. http://dx.doi.org/10.1016/j.bushor.2020.01.001

Further perspectives on pandemics and climate change

by

I have recently been asked whether the present corona pandemic will have any consequence on climate change. Gavin has already discussed the coronavirus and climate here on RealClimate, and I like to follow up on his post.

Rather than emphasising analogies, I would highlight additional common denominators between the present world-wide Covid-19 pandemic and climate change.

[Read more…] about Further perspectives on pandemics and climate change

Why not use a clever mathematical trick?

by 

There is a clever mathematical trick for comparing different data sets, but it does not seem to be widely used. It is based on so-called empirical orthogonal functions (EOFs), which Edward Lorenz described in a Massachusetts Institute of Technology (MIT) scientific report from 1956. The EOFs are similar to principal component analysis (PCA). 

The EOFs and PCAs provide patterns of spatio-temporal covariance structure. Usually these techniques are applied to datasets with many parallel variables to show coherent patterns of variability. Myles Allen used to lecture on EOFs at Oxford University about twenty years ago and convinced me about their value. Many scientists do indeed use EOFs to analyse their data. 

It is not that there is little use of EOFs (they are widely used), but the question is how the EOFs are used and how the results are interpreted. I learned that EOFs can be used in many different ways from Doug Nychka, when I visited University Corporation for Atmospheric Research (UCAR) in 2011.

The clever trick is to apply these techniques to data compiled from more than one source of data. When used this way, the technique is labelled “common EOFs” or “common PCA”. There are some scientific studies that have made use of common EOFs or common PCA, such as Flurry (1988), Barnett (1999), Sengupta & Boyle (1993), Benestad (2001), and Gilett et al (2002). 

Nevertheless, a Scholar Google recent search with “common EOFs” only gave 101 hits (2020-03-05). I find this low interest for this technique a bit puzzling, since it in many ways has lots in common to machine learning and artificial intelligence (AI), both which are hot topics these days. 

Common EOFs are also particularly useful for quantifying local effects of global warming through a process known as empirical-statistical downscaling (ESD). It's pity that common EOFs aren't even mentioned in the recent textbook on ESD by Maraun and Widmann (2019)  (they are discussed in Benestad et al. (2008)).

Figure. Examples showing how common EOFs can be used to compare the annual cycle in T(2m) in the upper set of panels and precipitation (lower panels) simulated by global climate models from the CMIP5 experiment (red) and compared with the ERAINT reanalysis (black).

 

The take-home message from these common EOFs, eigenvalues and principal components, is that the models do reproduce the large-scale patterns in the mean annual cycle. For those interested, common EOFs can easily be calculated with the R-based tool: 

github.com/metno/esd.

References

  1. R.E. Benestad, "A comparison between two empirical downscaling strategies", International Journal of Climatology, vol. 21, pp. 1645-1668, 2001. http://dx.doi.org/10.1002/joc.703
  2. N.P. Gillett, F.W. Zwiers, A.J. Weaver, G.C. Hegerl, M.R. Allen, and P.A. Stott, "Detecting anthropogenic influence with a multi‐model ensemble", Geophysical Research Letters, vol. 29, 2002. http://dx.doi.org/10.1029/2002GL015836