Hurricane dynamics and rapid intensification via dynamical systems indicators

2021 ◽  
Author(s):  
Davide Faranda ◽  
Gabriele Messori ◽  
Pascal Yiou ◽  
Soulivanh Thao ◽  
Flavio Pons ◽  
...  
Keyword(s):  
Dynamical System ◽  
Climate Models ◽  
Numerical Models ◽  
Atmospheric Dynamics ◽  
Rapid Intensification ◽  
Rotational Mode ◽  
Chaotic Dynamical System ◽  
Dynamical Properties ◽  
Low Dimensional ◽  
Bose Einstein

<p>Although the lifecycle of hurricanes is well understood, it is a struggle to represent their dynamics in numerical models, under both present and future climates. We consider the atmospheric circulation as a chaotic dynamical system, and show that the formation of a hurricane corresponds to a reduction of the phase space of the atmospheric dynamics to a low-dimensional state. This behavior is typical of Bose-Einstein condensates. These are states of the matter where all particles have the same dynamical properties. For hurricanes, this corresponds to a "rotational mode" around the eye of the cyclone, with all air parcels effectively behaving as spins oriented in a single direction. This finding paves the way for new parametrisations when simulating hurricanes in numerical climate models.</p>

scholarly journals Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Sergei A. Soldatenko
Keyword(s):  
Dynamical System ◽  
Optimal Control ◽  
Control Problem ◽  
Large Scale ◽  
Atmospheric Dynamics ◽  
Climate System ◽  
Chaotic Dynamical System ◽  
Weather And Climate ◽  
Earth’S Climate ◽  
Climate Manipulation

The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.

A brief discussion of the history, strengths and limitations of conceptual climate models for pre-Quaternary time

1993 ◽  
Vol 341 (1297) ◽  
pp. 263-266 ◽  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Early Stage ◽  
Numerical Models ◽  
Continental Drift ◽  
Structural Data ◽  
Atmospheric Dynamics ◽  
Climatic Data ◽  
Late Mesozoic ◽  
Zonal Model

Although it has been recognized at least since the time of Darwin and Agassiz that climate has varied significantly over geologic time, the study of global palaeoclimate did not come into its own until the theory of continental drift became ascendant. Initial studies in the early 1960s used climate models to test the reconstructions of continental positions. These studies, many collected in a pair of symposium volumes edited by A. E. M. Nairn, used a zonal model of climate or simple modifications thereof to predict how certain palaeoclimatic indicators - principally evaporites, coals, carbonates, red beds, and eolian sandstones - should be distributed on the continents through time if the continental reconstructions were correct. Even at that early stage in the development of continental reconstructions, past patterns of sedimentation were more clearly explained than had previously been the case. Continental reconstructions eventually began to stabilize, at least with respect to the major plates, in the late 1970s. Most of the information for positioning the continents came from paleomagnetic and structural data, but some elements of continental reconstructions relied heavily on climatic data - and the zonal climate model - for positioning. Nevertheless, it was at this time that studies of global palaeoclimate, independent of the concerns about the positions of the continents, could begin in earnest. A primary need was independence of the continental reconstructions from palaeoclimatic data, an ideal even now fully realized only for the late Mesozoic and Cenozoic. The term ‘conceptual climate model’ was coined by J . E. Kutzbach in reference to models published in the early 1980s. Like numerical models, conceptual climate models are based on the fundamentals of atmospheric circulation as determined from studies of the modern climate system, without explicitly treating atmospheric dynamics. They are reproducible and useful for developing an understanding of major changes in climate patterns driven by the changing positions of the continents. Despite their simplicity and non-explicit treatment of atmospheric dynamics, conceptual climate models have proved to be surprisingly robust in that the patterns predicted by explicitly dynamical models are similar for any given geologic period.

On the Potential for Entangled States Between Chaotic Systems

2014 ◽  
Vol 24 (06) ◽  
pp. 1450077 ◽  
Author(s):  
Matthew A. Morena ◽  
Kevin M. Short
Keyword(s):  
Dynamical System ◽  
Periodic Orbits ◽  
Chaotic Systems ◽  
Entangled States ◽  
Future Research ◽  
Unstable Periodic Orbits ◽  
Qualitative Information ◽  
Chaotic Dynamical System ◽  
Naturally Occurring ◽  
External Intervention

We report on the tendency of chaotic systems to be controlled onto their unstable periodic orbits in such a way that these orbits are stabilized. The resulting orbits are known as cupolets and collectively provide a rich source of qualitative information on the associated chaotic dynamical system. We show that pairs of interacting cupolets may be induced into a state of mutually sustained stabilization that requires no external intervention in order to be maintained and is thus considered bound or entangled. A number of properties of this sort of entanglement are discussed. For instance, should the interaction be disturbed, then the chaotic entanglement would be broken. Based on certain properties of chaotic systems and on examples which we present, there is further potential for chaotic entanglement to be naturally occurring. A discussion of this and of the implications of chaotic entanglement in future research investigations is also presented.

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

<p>Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.</p><p>Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.</p><p>We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.</p>

Northeast Atlantic storminess in centennial reanalyses

2021 ◽  
Author(s):  
Oliver Krueger ◽  
Frauke Feser ◽  
Christopher Kadow ◽  
Ralf Weisse
Keyword(s):  
Climate Models ◽  
Numerical Models ◽  
Geostrophic Wind ◽  
Model Systems ◽  
Storm Activity ◽  
Northeast Atlantic ◽  
Wind Speeds ◽  
Long Term Trends ◽  
Storm Index

<p>Global atmospheric reanalyses are commonly applied for the validation of climate models, diagnostic studies, and driving higher resolution numerical models with the emphasis on assessing climate variability and long-term trends. Over recent years, longer reanalyses spanning a period of more than hundred years have become available. In this study, the variability and long-term trends of storm activity is assessed over the northeast Atlantic in modern centennial reanalysis datasets, namely ERA-20cm, ERA-20c, CERA-20c, and the 20CR-reanalysis suite with 20CRv3 being the most recent one. All reanalyses, except from ERA-20cm, assimilate surface pressure observations, whereby ERA-20C and CERA-20c additionally assimilate surface winds. For the assessment, the well-established storm index of higher annual percentiles of geostrophic wind speeds derived from pressure observations at sea level over a relatively densely monitored marine area is used.</p><p>The results indicate that the examined centennial reanalyses are not able to represent long-term trends of storm activity over the northeast Atlantic, particularly in the earlier years of the period examined when compared with the geostrophic wind index based on pressure observations. Moreover, the reanalyses show inconsistent long-term behaviour when compared with each other. Only in the latter half of the 20th century, the variability of reanalysed and observed storminess time series starts to agree with each other. Additionally, 20CRv3, the most recent centennial reanalysis examined, shows markedly improved results with increased uncertainty, albeit multidecadal storminess variability does not match observed values in earlier times before about 1920.</p><p>The behaviour shown by the centennial reanalyses are likely caused by the increasing number of assimilated observations, changes in the observational databases used, and the different underlying numerical model systems. Furthermore, the results derived from the ERA-20cm reanalysis that does not assimilate any pressure or wind observations suggests that the variability and uncertainty of storminess over the northeast Atlantic is high making it difficult to determine storm activity when numerical models are not bound by observations. The results of this study imply and reconfirm previous findings that the assessment of long-term storminess trends and variability in centennial reanalyses remains a rather delicate matter, at least for the northeast Atlantic region.</p>

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