Simplicity amid Complexity Isaac Held Science 343, 1206 (2014); DOI: 10.1126/science.1248447
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The following resources related to this article are available online at www.sciencemag.org (this information is current as of April 13, 2014 ): Updated information and services, including high-resolution figures, can be found in the online version of this article at: http://www.sciencemag.org/content/343/6176/1206.full.html This article cites 12 articles, 7 of which can be accessed free: http://www.sciencemag.org/content/343/6176/1206.full.html#ref-list-1 This article appears in the following subject collections: Atmospheric Science http://www.sciencemag.org/cgi/collection/atmos
Science (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. Copyright 2014 by the American Association for the Advancement of Science; all rights reserved. The title Science is a registered trademark of AAAS.
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PERSPECTIVES CLIMATE CHANGE
Simplicity Amid Complexity
Despite the complexity of Earth’s climate system, the influence of human activities on climate can be identified and predicted.
W
e live in interesting times as we watch diverse effects of human activities on Earth’s climate emerge from natural variability. In predicting the outcome of this evolving inadvertent experiment, climate science faces many challenges, some of which have been outlined in this series of Science Perspectives (1–6 ): reducing the uncertainty in climate sensitivity; explaining the recent slowdown in the rate of warming and its implications for understanding internal variability; uncovering the factors that control how and where the land will become drier as it warms; quantifying the cooling due to anthropogenic aerosols; explaining the curious evolution of atmospheric methane; and predicting changes in extreme weather. In addition to these challenges, the turbulent and chaotic atmospheric and oceanic flows seemingly limit predictability on various time scales. Is the climate system just too complex for useful prediction? One response to the claim that multidecadal prediction is futile is to point to progress on each of these challenges (1–6 ). More fundamentally, an emphasis on complexity in the climate system must be balanced by recognition of emergent simplicity. The seasonal cycle provides a useful counterpoint. An individual year’s temperature record is a consequence of chaotic weather superposed on a relatively simple and smooth underlying cycle. Watching temperatures change during a few weeks in the spring does not affect confidence that typical summer temperatures will eventually emerge. Climate models paint an analogous picture for the evolution of climate over decades to centuries: a superposition of internal variability and an externally forced component containing a natural part (solar variations and volcanoes) and a part due to human activities that, to first approximation, is a linear superposition of responses to different forcing agents such NOAA–Geophysical Fluid Dynamics Laboratory, Forrestal Campus, Princeton, NJ 08540, USA. E-mail: isaac.held@ noaa.gov
1206
as CO2, methane, and aerosols. Unlike students of the seasonal cycle, students of climate change do not have the luxury of studying multiple realizations of their experiment, but can only observe the initial stages of a single realization. Thus, the attribution problem—the separation of the forced change from internal variability in observations and the partitioning of this forced component into parts due to different agents such as the well-mixed greenhouse gases or aerosols— is a tough challenge. But attribution leads directly to prediction of the forced response if the case can be made that the response is
simple enough for past trends to strongly constrain future evolution. Basing decisions on predictions of forced climate change is formally analogous to using knowledge of the normal climatological seasonal cycle to inform vacation plans, ignoring any weather predictions. Of course, we have much greater confidence in our knowledge of the climatological seasonal cycle than in predictions of forced climate change. The challenge to climate change research is to increase the credibility of the forced responses that theories and models predict, and to characterize internal variability well enough to appre-
ciate which aspects of these forced response have already emerged from the background of internal variability and which are likely to emerge in the future. Any skill in predicting multidecadal internal variability on top of this forced response is icing on the cake. Any strong nonlinearity in the forced response or abrupt shifts in the climate would provide special challenges. For example, suppose a model predicts distinctive atmospheric circulations and feedbacks to arise in an ice-free Arctic that have no close counterpart before that threshold is passed (7). What will provide credibility to a prediction of an abrupt forced climate change of this type, or the credibility of any prediction P that is not backed by attribution of recent trends? Paleoclimate reconstructions should provide some guidance and perhaps even close analogs. But, ultimately, it may just be necessary to rely on understanding the underlying physics. For example, suppose one can argue, based on this understanding, that some other aspect O of the climate depends on the same processes that come into play in the climate change P. If observations exist to evaluate the simulation of O, the result will be indirect evidence for P. This approach is being explored in several climate change contexts (8). The models used to simulate the climate are themselves complex, chaotic dynamical systems. To work with them effectively requires not only the careful examination of alternative formulations of these comprehensive models but also the construction of a hierarchy of models in which elements of complexity are added sequentially. This approach is similar in spirit to that used in biology, where a hierarchy of model organisms—from bacteria to fruit fly to zebrafish to mouse to chimpanzee— is used to build an understanding of human biology (9). A good example of the use of a hierarchy of models is provided by research on the
14 MARCH 2014 VOL 343 SCIENCE www.sciencemag.org Published by AAAS
CREDIT: PETER AND MARIA HOEY/WWW.PETERHOEY.COM
Isaac Held
PERSPECTIVES effect of the Antarctic ozone hole on the surface westerlies in the Southern Hemisphere. Observational studies showed that the westerlies shifted poleward by several degrees of latitude in recent decades, mainly in the Austral summer, and made a plausible connection to the development of the ozone hole (10). Comprehensive models provided important confirmation that the ozone hole does move the westerlies poleward (11). A variety of more idealized models are being used to explore the pathways through which changes in the stratosphere modify the surface winds, demonstrating that the poleward shift of the westerlies due to cooling of the polar stratosphere can be isolated from other parts of the climate problem and related to fundamental theories of atmospheric dynamics (12). Increasing CO2 concentrations also push the mid-latitude surface westerlies poleward in climate models, complicating both the quantitative attribution of the observed shift
(11) and the predictions of how the westerlies will evolve in the future as the ozone hole heals and greenhouse gases continue to accumulate. However, both comprehensive and idealized climate models indicate that the effects on the westerlies of greenhouse gases and the ozone hole are linearly additive to a first approximation. An underlying simplicity in the forced climate change emerges here as well, making prediction plausible. A creative tension between simulation and understanding, between accepting complexity and searching for simplicity, is present in many challenging scientific problems. Climate science provides an excellent example of this tension. The most advanced comprehensive climate models effectively represent the current ability to simulate the climate system, and it is natural and appropriate to take the output of those models as the basis for predicting the future climate. However, it is the understanding of these responses—an under-
standing that depends on the presence of an emergent simplicity in the forced response— which provides a level of confidence that justifies advising policy-makers and the public to pay heed to these predictions. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
G. Hegerl, P. Stott, Science 343, 844 (2014). A. Clement, P. DiNezio, Science 343, 976 (2014). S. Sherwood, Q. Fu, Science 343, 737 (2014). D. Rosenfeld, S. Sherwood, R. Wood, L. Donner, Science 343, 379 (2014). E. G. Nisbet, E. J. Dlugokencky, P. Bousquet, Science 343, 493 (2014). G. A. Vecchi, G. Villarini, Science 343, 618 (2014). D. S. Abbott, E. Tziperman, J. Atmos. Sci. 66, 519 (2009). S. C. Sherwood, S. Bony, J.-L. Dufresne, Nature 505, 37 (2014). I. M. Held, Bull. Am. Meteorol. Soc. 86, 1609 (2005). D. W. J. Thompson, S. Solomon, Science 296, 895 (2002). S.-W. Son et al., J. Geophys. Res. 115, D00M07 (2010). C. I. Garfinkel, D.-Y. Waugh, E. P. Gerber, J. Clim. 26, 2077 (2013). 10.1126/science.1248447
MOLECULAR BIOLOGY
Internal mRNA Methylation Finally Finds Functions
Methylation of internal adenosine residues in messenger RNA (mRNA) modulates mRNA metabolism in both the nucleus and cytoplasm.
Timothy W. Nilsen
M
odification of internal adenosines in messenger RNA (mRNA) by methylation of the N6 position 6 (m A) was first observed almost four decades ago. Early work demonstrated that the m6A modification was quite common, occurring at an estimated frequency of three to five residues per mRNA. Nevertheless, the function, if any, of this modification remained enigmatic. The cloning in 1997 of a subunit of the RNA methylase complex (1) was followed by a period of fitful inactivity before the field reawakened in 2011 with the discovery of an enzyme, FTO (fat mass and obesity-associated protein), that was shown to catalyze the demethylation of internal m6A residues (2). The existence of a demethylase and the demonstration that m6A levels were raised when the enzyme was knocked down strongly suggested that at least some m6A modifications were reversible and might be subject to dynamic regulation. Since then, a series of papers have appeared in rapid succession, together providing a wealth of unequivocal Center for RNA Molecular Biology, Case Western Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, OH 44106, USA. E-mail: [email protected]
evidence for m6A function. But these findings still have not led to a coherent picture of the number and variety of functions of the m6A modification. Two recent RNA “methylome” studies (3, 4) provide a transcriptome-wide map of m6A-modified mRNAs. Both report the presence of m6A in about 7000 mRNAs, indicating that the modification is fairly promiscuous with regard to mRNA targets. However, methylation is highly selective when considering which specific sites are modified.
Although both studies showed that methylation sites are largely confined to the consensus sequence Pu[G>A]m6AC[A/C/U], only about 10% of sites conforming to this consensus are actually modified. Neither study was able to determine the stoichiometry of any specific modified site, nor could clusters of modified sites be identified. Both studies showed enrichment of modification sites near stop codons; however, one study saw enrichment in long internal exons while the other saw enrichment in 3′ untranslated regions. Additionally, one study found elevated levels of m6A in the brain and mRNA AAAA the other study did not. The reasons for these discrepancies are not A obvious. Nevertheless, both studies Demethylase Methylase found that modification sites were FTO, ALKBH5 METTL3 well conserved between human and mouse transcriptomes—a findm6A ing strongly suggestive of biological function. Indeed, knockdown of ? YTHDF2 the m6A methylase (3) resulted in AAAA mRNA large-scale alterations in splicing Alternative Other? mRNA patterns, consistent with a striking splicing stability enrichment of m6A modifications Methylating RNA regulates its function. A schematic diagram of within alternatively spliced exons the RNA m6A methylation cycle. METTL3, methyltransferase-like 3. (see the figure), with constitutive
www.sciencemag.org SCIENCE VOL 343 14 MARCH 2014 Published by AAAS
1207
This copy is for your personal, non-commercial use only.
If you wish to distribute this article to others, you can order high-quality copies for your colleagues, clients, or customers by clicking here.
The following resources related to this article are available online at www.sciencemag.org (this information is current as of April 13, 2014 ): Updated information and services, including high-resolution figures, can be found in the online version of this article at: http://www.sciencemag.org/content/343/6176/1206.full.html This article cites 12 articles, 7 of which can be accessed free: http://www.sciencemag.org/content/343/6176/1206.full.html#ref-list-1 This article appears in the following subject collections: Atmospheric Science http://www.sciencemag.org/cgi/collection/atmos
Science (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. Copyright 2014 by the American Association for the Advancement of Science; all rights reserved. The title Science is a registered trademark of AAAS.
Downloaded from www.sciencemag.org on April 13, 2014
Permission to republish or repurpose articles or portions of articles can be obtained by following the guidelines here.
PERSPECTIVES CLIMATE CHANGE
Simplicity Amid Complexity
Despite the complexity of Earth’s climate system, the influence of human activities on climate can be identified and predicted.
W
e live in interesting times as we watch diverse effects of human activities on Earth’s climate emerge from natural variability. In predicting the outcome of this evolving inadvertent experiment, climate science faces many challenges, some of which have been outlined in this series of Science Perspectives (1–6 ): reducing the uncertainty in climate sensitivity; explaining the recent slowdown in the rate of warming and its implications for understanding internal variability; uncovering the factors that control how and where the land will become drier as it warms; quantifying the cooling due to anthropogenic aerosols; explaining the curious evolution of atmospheric methane; and predicting changes in extreme weather. In addition to these challenges, the turbulent and chaotic atmospheric and oceanic flows seemingly limit predictability on various time scales. Is the climate system just too complex for useful prediction? One response to the claim that multidecadal prediction is futile is to point to progress on each of these challenges (1–6 ). More fundamentally, an emphasis on complexity in the climate system must be balanced by recognition of emergent simplicity. The seasonal cycle provides a useful counterpoint. An individual year’s temperature record is a consequence of chaotic weather superposed on a relatively simple and smooth underlying cycle. Watching temperatures change during a few weeks in the spring does not affect confidence that typical summer temperatures will eventually emerge. Climate models paint an analogous picture for the evolution of climate over decades to centuries: a superposition of internal variability and an externally forced component containing a natural part (solar variations and volcanoes) and a part due to human activities that, to first approximation, is a linear superposition of responses to different forcing agents such NOAA–Geophysical Fluid Dynamics Laboratory, Forrestal Campus, Princeton, NJ 08540, USA. E-mail: isaac.held@ noaa.gov
1206
as CO2, methane, and aerosols. Unlike students of the seasonal cycle, students of climate change do not have the luxury of studying multiple realizations of their experiment, but can only observe the initial stages of a single realization. Thus, the attribution problem—the separation of the forced change from internal variability in observations and the partitioning of this forced component into parts due to different agents such as the well-mixed greenhouse gases or aerosols— is a tough challenge. But attribution leads directly to prediction of the forced response if the case can be made that the response is
simple enough for past trends to strongly constrain future evolution. Basing decisions on predictions of forced climate change is formally analogous to using knowledge of the normal climatological seasonal cycle to inform vacation plans, ignoring any weather predictions. Of course, we have much greater confidence in our knowledge of the climatological seasonal cycle than in predictions of forced climate change. The challenge to climate change research is to increase the credibility of the forced responses that theories and models predict, and to characterize internal variability well enough to appre-
ciate which aspects of these forced response have already emerged from the background of internal variability and which are likely to emerge in the future. Any skill in predicting multidecadal internal variability on top of this forced response is icing on the cake. Any strong nonlinearity in the forced response or abrupt shifts in the climate would provide special challenges. For example, suppose a model predicts distinctive atmospheric circulations and feedbacks to arise in an ice-free Arctic that have no close counterpart before that threshold is passed (7). What will provide credibility to a prediction of an abrupt forced climate change of this type, or the credibility of any prediction P that is not backed by attribution of recent trends? Paleoclimate reconstructions should provide some guidance and perhaps even close analogs. But, ultimately, it may just be necessary to rely on understanding the underlying physics. For example, suppose one can argue, based on this understanding, that some other aspect O of the climate depends on the same processes that come into play in the climate change P. If observations exist to evaluate the simulation of O, the result will be indirect evidence for P. This approach is being explored in several climate change contexts (8). The models used to simulate the climate are themselves complex, chaotic dynamical systems. To work with them effectively requires not only the careful examination of alternative formulations of these comprehensive models but also the construction of a hierarchy of models in which elements of complexity are added sequentially. This approach is similar in spirit to that used in biology, where a hierarchy of model organisms—from bacteria to fruit fly to zebrafish to mouse to chimpanzee— is used to build an understanding of human biology (9). A good example of the use of a hierarchy of models is provided by research on the
14 MARCH 2014 VOL 343 SCIENCE www.sciencemag.org Published by AAAS
CREDIT: PETER AND MARIA HOEY/WWW.PETERHOEY.COM
Isaac Held
PERSPECTIVES effect of the Antarctic ozone hole on the surface westerlies in the Southern Hemisphere. Observational studies showed that the westerlies shifted poleward by several degrees of latitude in recent decades, mainly in the Austral summer, and made a plausible connection to the development of the ozone hole (10). Comprehensive models provided important confirmation that the ozone hole does move the westerlies poleward (11). A variety of more idealized models are being used to explore the pathways through which changes in the stratosphere modify the surface winds, demonstrating that the poleward shift of the westerlies due to cooling of the polar stratosphere can be isolated from other parts of the climate problem and related to fundamental theories of atmospheric dynamics (12). Increasing CO2 concentrations also push the mid-latitude surface westerlies poleward in climate models, complicating both the quantitative attribution of the observed shift
(11) and the predictions of how the westerlies will evolve in the future as the ozone hole heals and greenhouse gases continue to accumulate. However, both comprehensive and idealized climate models indicate that the effects on the westerlies of greenhouse gases and the ozone hole are linearly additive to a first approximation. An underlying simplicity in the forced climate change emerges here as well, making prediction plausible. A creative tension between simulation and understanding, between accepting complexity and searching for simplicity, is present in many challenging scientific problems. Climate science provides an excellent example of this tension. The most advanced comprehensive climate models effectively represent the current ability to simulate the climate system, and it is natural and appropriate to take the output of those models as the basis for predicting the future climate. However, it is the understanding of these responses—an under-
standing that depends on the presence of an emergent simplicity in the forced response— which provides a level of confidence that justifies advising policy-makers and the public to pay heed to these predictions. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
G. Hegerl, P. Stott, Science 343, 844 (2014). A. Clement, P. DiNezio, Science 343, 976 (2014). S. Sherwood, Q. Fu, Science 343, 737 (2014). D. Rosenfeld, S. Sherwood, R. Wood, L. Donner, Science 343, 379 (2014). E. G. Nisbet, E. J. Dlugokencky, P. Bousquet, Science 343, 493 (2014). G. A. Vecchi, G. Villarini, Science 343, 618 (2014). D. S. Abbott, E. Tziperman, J. Atmos. Sci. 66, 519 (2009). S. C. Sherwood, S. Bony, J.-L. Dufresne, Nature 505, 37 (2014). I. M. Held, Bull. Am. Meteorol. Soc. 86, 1609 (2005). D. W. J. Thompson, S. Solomon, Science 296, 895 (2002). S.-W. Son et al., J. Geophys. Res. 115, D00M07 (2010). C. I. Garfinkel, D.-Y. Waugh, E. P. Gerber, J. Clim. 26, 2077 (2013). 10.1126/science.1248447
MOLECULAR BIOLOGY
Internal mRNA Methylation Finally Finds Functions
Methylation of internal adenosine residues in messenger RNA (mRNA) modulates mRNA metabolism in both the nucleus and cytoplasm.
Timothy W. Nilsen
M
odification of internal adenosines in messenger RNA (mRNA) by methylation of the N6 position 6 (m A) was first observed almost four decades ago. Early work demonstrated that the m6A modification was quite common, occurring at an estimated frequency of three to five residues per mRNA. Nevertheless, the function, if any, of this modification remained enigmatic. The cloning in 1997 of a subunit of the RNA methylase complex (1) was followed by a period of fitful inactivity before the field reawakened in 2011 with the discovery of an enzyme, FTO (fat mass and obesity-associated protein), that was shown to catalyze the demethylation of internal m6A residues (2). The existence of a demethylase and the demonstration that m6A levels were raised when the enzyme was knocked down strongly suggested that at least some m6A modifications were reversible and might be subject to dynamic regulation. Since then, a series of papers have appeared in rapid succession, together providing a wealth of unequivocal Center for RNA Molecular Biology, Case Western Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, OH 44106, USA. E-mail: [email protected]
evidence for m6A function. But these findings still have not led to a coherent picture of the number and variety of functions of the m6A modification. Two recent RNA “methylome” studies (3, 4) provide a transcriptome-wide map of m6A-modified mRNAs. Both report the presence of m6A in about 7000 mRNAs, indicating that the modification is fairly promiscuous with regard to mRNA targets. However, methylation is highly selective when considering which specific sites are modified.
Although both studies showed that methylation sites are largely confined to the consensus sequence Pu[G>A]m6AC[A/C/U], only about 10% of sites conforming to this consensus are actually modified. Neither study was able to determine the stoichiometry of any specific modified site, nor could clusters of modified sites be identified. Both studies showed enrichment of modification sites near stop codons; however, one study saw enrichment in long internal exons while the other saw enrichment in 3′ untranslated regions. Additionally, one study found elevated levels of m6A in the brain and mRNA AAAA the other study did not. The reasons for these discrepancies are not A obvious. Nevertheless, both studies Demethylase Methylase found that modification sites were FTO, ALKBH5 METTL3 well conserved between human and mouse transcriptomes—a findm6A ing strongly suggestive of biological function. Indeed, knockdown of ? YTHDF2 the m6A methylase (3) resulted in AAAA mRNA large-scale alterations in splicing Alternative Other? mRNA patterns, consistent with a striking splicing stability enrichment of m6A modifications Methylating RNA regulates its function. A schematic diagram of within alternatively spliced exons the RNA m6A methylation cycle. METTL3, methyltransferase-like 3. (see the figure), with constitutive
www.sciencemag.org SCIENCE VOL 343 14 MARCH 2014 Published by AAAS
1207
