scholarly journals Minimal dynamical systems model of the northern hemisphere jet stream via embedding of climate data

Author(s):  
Davide Faranda ◽  
Yuzuru Sato ◽  
Gabriele Messori ◽  
Nicholas R. Moloney ◽  
Pascal Yiou

Abstract. We derive a minimal dynamical model for the northern hemisphere mid-latitude jet dynamics by embedding atmospheric data, and investigate its properties (bifurcation structure, stability, local dimensions) for different atmospheric flow regimes. We derive our model according to the following steps: i) obtain a 1-D description of the mid-latitude jet-stream by computing the position of the jet at each longitude using the ERA-Interim reanalysis, ii) use the embedding procedure to derive a map of the local jet position dynamics, iii) introduce the coupling and stochastic effects deriving from both atmospheric turbulence and topographic disturbances to the jet. We then analyze the dynamical properties of the model in different regimes: i) one that gives the closest representation of the properties extracted from real data, ii) one featuring a stronger jet (strong coupling), iii) one featuring a weaker jet (low coupling), iv) modified topography. We argue that such a simple model provides a useful description of the dynamical properties of the atmospheric jet.

2019 ◽  
Vol 10 (3) ◽  
pp. 555-567 ◽  
Author(s):  
Davide Faranda ◽  
Yuzuru Sato ◽  
Gabriele Messori ◽  
Nicholas R. Moloney ◽  
Pascal Yiou

Abstract. We derive a minimal dynamical systems model for the Northern Hemisphere midlatitude jet dynamics by embedding atmospheric data and by investigating its properties (bifurcation structure, stability, local dimensions) for different atmospheric flow regimes. The derivation is a three-step process: first, we obtain a 1-D description of the midlatitude jet stream by computing the position of the jet at each longitude using ERA-Interim. Next, we use the embedding procedure to derive a map of the local jet position dynamics. Finally, we introduce the coupling and stochastic effects deriving from both atmospheric turbulence and topographic disturbances to the jet. We then analyze the dynamical properties of the model in different regimes: one that gives the closest representation of the properties extracted from real data; one featuring a stronger jet (strong coupling); one featuring a weaker jet (weak coupling); and one with modified topography. Our model, notwithstanding its simplicity, provides an instructive description of the dynamical properties of the atmospheric jet.


Author(s):  
Jennifer Francis ◽  
Natasa Skific

The effects of rapid Arctic warming and ice loss on weather patterns in the Northern Hemisphere is a topic of active research, lively scientific debate and high societal impact. The emergence of Arctic amplification—the enhanced sensitivity of high-latitude temperature to global warming—in only the last 10–20 years presents a challenge to identifying statistically robust atmospheric responses using observations. Several recent studies have proposed and demonstrated new mechanisms by which the changing Arctic may be affecting weather patterns in mid-latitudes, and these linkages differ fundamentally from tropics/jet-stream interactions through the transfer of wave energy. In this study, new metrics and evidence are presented that suggest disproportionate Arctic warming—and resulting weakening of the poleward temperature gradient—is causing the Northern Hemisphere circulation to assume a more meridional character (i.e. wavier), although not uniformly in space or by season, and that highly amplified jet-stream patterns are occurring more frequently. Further analysis based on self-organizing maps supports this finding. These changes in circulation are expected to lead to persistent weather patterns that are known to cause extreme weather events. As emissions of greenhouse gases continue unabated, therefore, the continued amplification of Arctic warming should favour an increased occurrence of extreme events caused by prolonged weather conditions.


2018 ◽  
Vol 180 ◽  
pp. 126-136 ◽  
Author(s):  
M.A. Chernigovskaya ◽  
B.G. Shpynev ◽  
K.G. Ratovsky ◽  
A.Yu. Belinskaya ◽  
A.E. Stepanov ◽  
...  

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1193
Author(s):  
Chuchu Xu ◽  
Mi Yan ◽  
Liang Ning ◽  
Jian Liu

The upper-level jet stream, a narrow band of maximum wind speed in the mid-latitude westerlies, exerts a considerable influence on the global climate by modulating the transport and distribution of momentum, heat and moisture. In this study by using four high-resolution models in the Paleoclimate Modelling Intercomparison Project phase 3, the changes of position and intensity of the northern hemisphere westerly jet at 200 hPa in summer during the mid-Holocene (MH), as well as the related mechanisms, are investigated. The four models show similar performance on the westerly jet. At the hemispheric scale, the simulated westerly jet has a poleward shift during the MH compared to the preindustrial period. The warming in arctic and cooling in the tropics during the MH are caused by the orbital changes of the earth and the precipitation changes, and it could lead to the weakened meridional temperature gradient and pressure gradient, which might account for the poleward shift of the westerly jet from the thermodynamic perspective. From the dynamic perspective, two maximum centers of eddy kinetic energy are simulated over the North Pacific and North Atlantic with the north deviation, which could cause the northward movement of the westerly jet. The weakening of the jet stream is associated with the change of the Hadley cell and the meridional temperature gradient. The largest weakening is over the Pacific Ocean where both the dynamic and the thermodynamic processes have weakening effects. The smallest weakening is over the Atlantic Ocean, and it is induced by the offset effects of dynamic processes and thermodynamic processes. The weakening over the Eurasia is mainly caused by the dynamic processes.


2017 ◽  
Vol 24 (4) ◽  
pp. 713-725 ◽  
Author(s):  
Davide Faranda ◽  
Gabriele Messori ◽  
M. Carmen Alvarez-Castro ◽  
Pascal Yiou

Abstract. Atmospheric dynamics are described by a set of partial differential equations yielding an infinite-dimensional phase space. However, the actual trajectories followed by the system appear to be constrained to a finite-dimensional phase space, i.e. a strange attractor. The dynamical properties of this attractor are difficult to determine due to the complex nature of atmospheric motions. A first step to simplify the problem is to focus on observables which affect – or are linked to phenomena which affect – human welfare and activities, such as sea-level pressure, 2 m temperature, and precipitation frequency. We make use of recent advances in dynamical systems theory to estimate two instantaneous dynamical properties of the above fields for the Northern Hemisphere: local dimension and persistence. We then use these metrics to characterize the seasonality of the different fields and their interplay. We further analyse the large-scale anomaly patterns corresponding to phase-space extremes – namely time steps at which the fields display extremes in their instantaneous dynamical properties. The analysis is based on the NCEP/NCAR reanalysis data, over the period 1948–2013. The results show that (i) despite the high dimensionality of atmospheric dynamics, the Northern Hemisphere sea-level pressure and temperature fields can on average be described by roughly 20 degrees of freedom; (ii) the precipitation field has a higher dimensionality; and (iii) the seasonal forcing modulates the variability of the dynamical indicators and affects the occurrence of phase-space extremes. We further identify a number of robust correlations between the dynamical properties of the different variables.


2011 ◽  
Vol 14 (04) ◽  
pp. 635-647 ◽  
Author(s):  
GIAN MARCO PALAMARA ◽  
VINKO ZLATIĆ ◽  
ANTONIO SCALA ◽  
GUIDO CALDARELLI

In this work we analyze the topological and dynamical properties of a simple model of complex food webs, namely the niche model. In order to underline competition among species, we introduce "prey" and "predators" weighted overlap graphs derived from the niche model and compare synthetic food webs with real data. Doing so, we find new tests for the goodness of synthetic food web models and indicate a possible direction of improvement for existing ones. We then exploit the weighted overlap graphs to define a competition kernel for Lotka–Volterra population dynamics and find that for such a model the stability of food webs decreases with its ecological complexity.


2012 ◽  
Vol 47 (3-4) ◽  
pp. 389-405 ◽  
Author(s):  
N. R. Samal ◽  
D. C. Pierson ◽  
E. Schneiderman ◽  
Y. Huang ◽  
J. S. Read ◽  
...  

Global Circulation Model values of mean daily air temperature, wind speed and solar radiation for the 2081–2100 period are used to produce change factors that are applied to a 39 year record of local meteorological data to produce future climate scenarios. These climate scenarios are used to drive two separate, but coupled models: the Generalized Watershed Loading Functions-Variable Source Area model in order to simulate reservoir tributary inflows, and a one-dimensional reservoir hydrothermal model used to evaluate changes in reservoir thermal structure in response to changes in meteorological forcing and changes in simulated inflow. Comparisons between simulations based on present-day climate data (baseline conditions) and future simulations (change-factor adjusted baseline conditions) are used to evaluate the development and breakdown of thermal stratification, as well as a number of metrics that describe reservoir thermal structure, stability and mixing. Both epilimnion and hypolimnion water temperatures are projected to increase. Indices of mixing and stability show changes that are consistent with the simulated changes in reservoir thermal structure. Simulations suggest that stratification will begin earlier and the reservoir will exhibit longer and more stable periods of thermal stratification under future climate conditions.


2021 ◽  
Author(s):  
Xiaona Chen ◽  
Shunlin Liang ◽  
Lian He ◽  
Yaping Yang ◽  
Cong Yin

Abstract. Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change due to its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among existing continental scale SCE products hampers its detailed studies. Using the latest Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free SCE covering the NH landmass for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. The development of GLASS SCE contains five steps. First, a decision tree algorithm with multiple threshold tests was applied to distinguish snow cover (NHSCE-D) with other land cover types from daily AVHRR-SR CDR. Second, gridcells with cloud cover and invalid observations were filled by two existing daily SCE products. The gap-filled gridcells were further merged with NHSCE-D to generate combined daily SCE over the NH (NHSCE-Dc). Third, an aggregation process was used to detect the maximum SCE and minimum gaps in each 8-day periods from NHSCE-Dc. Forth, the gaps after aggregation process were further filled by the climatology of snow cover probability to generate the gap-free GLASS SCE. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r = 0.61, p < 0.05) and MOD10C2 during 2001–2019 (r = 0.97, p < 0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data are available at https://doi.org/10.5281/zenodo.5775238 (Chen et al. 2021).


Author(s):  
Luciana Romani ◽  
Elaine de Sousa ◽  
Marcela Ribeiro ◽  
Ana de Ávila ◽  
Jurandir Zullo ◽  
...  

This chapter discusses how to take advantage of computational models to analyze and extract useful information from time series of climate data and remote sensing images. This kind of data has been used for researching on climate changes, as well as to help on improving yield forecasting of agricultural crops and increasing the sustainable usage of the soil. The authors present three techniques based on the Fractal Theory, data streams and time series mining: the FDASE algorithm, to identify correlated attributes; a method that combines intrinsic dimension measurements with statistical analysis, to monitor evolving climate and remote sensing data; and the CLIPSMiner algorithm applied to multiple time series of continuous climate data, to identify relevant and extreme patterns. The experiments with real data show that data mining is a valuable tool to help agricultural entrepreneurs and government on monitoring sugar cane areas, helping to make the production more useful to the country and to the environment.


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