scholarly journals Extratropical low-frequency variability with ENSO forcing: a reduced-order coupled model study  

2021 ◽  
Author(s):  
Stéphane Vannitsem ◽  
Jonathan Demaeyer ◽  
Michael Ghil
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Coupled Model ◽  
Ensemble Averaging ◽  
Reduced Order ◽  
Low Frequency Variability ◽  
Coupling Parameters ◽  
Parameter Ranges ◽  
The Impact

<p>The impact of the El Niño-Southern Oscillation (ENSO) on the extratropics is investigated in an idealized, reduced-order model that has a tropical and an extratropical module. Unidirectional forcing is used to mimic the atmospheric bridge between the tropics and the extratropics. The variability of the coupled ocean--atmosphere extratropical module is then investigated through the analysis of its pullback attractors (PBA). This analysis focuses on two ENSO-type forcings generated by the tropical module, one periodic and one aperiodic.</p><p> </p><p>For a substantial range of coupling parameters, multiple chaotic PBAs are found to coexist for the same set of parameter values. Different types of extratropical low-frequency variability are associated with each PBA over the parameter ranges explored. For periodic ENSO forcing, the coexisting PBAs are nonlinearly stable, while for the chaotic forcing, they are unstable and certain extratropical perturbations induce transitions between the PBAs. These distinct stability properties may have profound consequences for extratropical climate predictions, provided they are confirmed by studies using comprehensive climate models. Thus, for instance, ensemble averaging may no longer be a valid approach to isolate the low-frequency variability signal.</p>

qgs: A flexible Python framework of reduced-order multiscale climate models

2021 ◽  
Author(s):  
Lesley De Cruz ◽  
Jonathan Demaeyer ◽  
Stéphane Vannitsem
Keyword(s):  
Open Source Software ◽  
Climate Models ◽  
Low Frequency ◽  
Atmospheric Dynamics ◽  
The Other ◽  
Research Use ◽  
Good Representation ◽  
Atmospheric Variability ◽  
Reduced Order ◽  
Low Frequency Variability

<p>In atmospheric and climate sciences, research and development is often first conducted with a simple idealized system like the Lorenz-<em>N</em> models (<em>N ∈</em> {63, 84, 96}) which are toy models of atmospheric variability. On the other hand, reduced-order spectral quasi-geostrophic models of the atmosphere with a sufficient number of modes offer a good representation of the dry atmospheric dynamics. They allow one to identify typical features of the atmospheric circulation, such as blocked and zonal circulation regimes, and low-frequency variability. However, these models are less often considered in literature, despite their demonstration of more realistic behavior.</p><p><strong>qgs</strong> (Demaeyer et al., 2020) aims to popularize these systems by providing a fast and easy-to-use Python framework for researchers and teachers to integrate this kind of model. The documentation makes it clear and efficient to handle the model, by explaining the equations and parameters and linking these to the code. </p><p>The choice to use Python was specifically made to facilitate its use in Jupyter Notebooks and with the multiple recent machine learning libraries that are available in this language.</p><p>In this talk, we will present the modeling capabilities of <strong>qgs</strong> and show its usage in a varieties of didactical and research use cases.</p><p><strong>Reference</strong></p><p>Demaeyer, J., De Cruz, L., & Vannitsem, S. (2020). qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software, 5(56), 2597, https://doi.org/10.21105/joss.02597 .</p>

scholarly journals Slow Modes of Global Temperature Variability and Their Impact on Climate Sensitivity Estimates

2021 ◽  
pp. 1-68
Author(s):  
Robert C. J. Wills ◽  
Kyle C. Armour ◽  
David S. Battisti ◽  
Cristian Proistosescu ◽  
Luke A. Parsons
Keyword(s):  
Climate Sensitivity ◽  
Energy Budget ◽  
High Latitude ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Coupled Model ◽  
Internal Variability ◽  
Minimal Impact ◽  
Radiative Feedback ◽  
The Impact

AbstractInternal climate variability confounds estimates of the climate response to forcing but offers an opportunity to examine the dynamics controlling Earth’s energy budget. This study analyzes the time-evolving impact of modes of low-frequency internal variability on global-mean surface temperature (GMST) and top-of-atmosphere (TOA) radiation in pre-industrial control simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6). The results show that the slow modes of variability with the largest impact on decadal GMST anomalies are focused in high-latitude ocean regions, where they have a minimal impact on global TOA radiation. When these regions warm, positive shortwave cloud and sea ice-albedo feedbacks largely cancel the negative feedback of outgoing longwave radiation, resulting in a weak net radiative feedback. As a consequence of the weak net radiative feedback, less energy is required to sustain these long-lived temperature anomalies. In contrast to these weakly radiating high-latitude modes, the El Niño-Southern Oscillation (ENSO) has a large impact on the global energy budget, such that it remains the dominant influence on global TOA radiation out to decadal and longer timescales, despite its primarily interannual timescale. These results show that on decadal and longer timescales, different processes control internal variability in GMST than control internal variability in global TOA radiation. The results are used to quantify the impact of low-frequency internal variability and ENSO on estimates of climate sensitivity from historical GMST and TOA-radiative-imbalance anomalies.

scholarly journals Shift Detection in Hydrological Regimes and Pluriannual Low-Frequency Streamflow Forecasting Using the Hidden Markov Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2058 ◽  
Author(s):  
Larissa Rolim ◽  
Francisco de Souza Filho
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Extreme Events ◽  
Hidden Markov ◽  
Low Frequency ◽  
Streamflow Forecasting ◽  
Hydrologic Time Series ◽  
Low Frequency Variability ◽  
The Impact

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year.

scholarly journals A Chronology of El Niño Events from Primary Documentary Sources in Northern Peru*

2008 ◽  
Vol 21 (9) ◽  
pp. 1948-1962 ◽  
Author(s):  
R. Garcia-Herrera ◽  
D. Barriopedro ◽  
E. Hernández ◽  
H. F. Diaz ◽  
R. R. Garcia ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Primary Sources ◽  
Proxy Data ◽  
Documentary Sources ◽  
Low Frequency Variability ◽  
Northern Peru

Abstract The authors present a chronology of El Niño (EN) events based on documentary records from northern Peru. The chronology, which covers the period 1550–1900, is constructed mainly from primary sources from the city of Trujillo (Peru), the Archivo General de Indias in Seville (Spain), and the Archivo General de la Nación in Lima (Peru), supplemented by a reassessment of documentary evidence included in previously published literature. The archive in Trujillo has never been systematically evaluated for information related to the occurrence of El Niño–Southern Oscillation (ENSO). Abundant rainfall and river discharge correlate well with EN events in the area around Trujillo, which is very dry during most other years. Thus, rain and flooding descriptors, together with reports of failure of the local fishery, are the main indicators of EN occurrence that the authors have searched for in the documents. A total of 59 EN years are identified in this work. This chronology is compared with the two main previous documentary EN chronologies and with ENSO indicators derived from proxy data other than documentary sources. Overall, the seventeenth century appears to be the least active EN period, while the 1620s, 1720s, 1810s, and 1870s are the most active decades. The results herein reveal long-term fluctuations in warm ENSO activity that compare reasonably well with low-frequency variability deduced from other proxy data.

The essential role of early-spring westerly wind burst in generating the centennial extreme 1997/98 El Niño

2021 ◽  
pp. 1-38
Author(s):  
Tao Lian ◽  
Dake Chen
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Coupled Model ◽  
Early Spring ◽  
Strong Nonlinearity ◽  
Westerly Wind ◽  
Enso Dynamics

AbstractWhile both intrinsic low-frequency atmosphere–ocean interaction and multiplicative burst-like event affect the development of the El Niño–Southern Oscillation (ENSO), the strong nonlinearity in ENSO dynamics has prevented us from separating their relative contributions. Here we propose an online filtering scheme to estimate the role of the westerly wind bursts (WWBs), a type of aperiodic burst-like atmospheric perturbation over the western-central tropical Pacific, in the genesis of the centennial extreme 1997/98 El Niño using the CESM coupled model. This scheme highlights the deterministic part of ENSO dynamics during model integration, and clearly demonstrates that the strong and long-lasting WWB in March 1997 was essential for generating the 1997/98 El Niño. Without this WWB, the intrinsic low-frequency coupling would have only produced a weak warm event in late 1997 similar to the 2014/15 El Niño.

Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

2013 ◽  
Vol 26 (1) ◽  
pp. 231-245 ◽  
Author(s):  
Michael Winton ◽  
Alistair Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
Larry W. Horowitz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
Historical Simulation ◽  
Model Version ◽  
Salinity Response ◽  
The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

scholarly journals Correction to: The impact of stochastic physics on the El Niño Southern Oscillation in the EC-Earth coupled model

2019 ◽  
Vol 53 (3-4) ◽  
pp. 2479-2479 ◽  
Author(s):  
Chunxue Yang ◽  
Hannah M. Christensen ◽  
Susanna Corti ◽  
Jost von Hardenberg ◽  
Paolo Davini
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Coupled Model ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Impact ◽  
Stochastic Physics

scholarly journals Climate models can correctly simulate the continuum of global-average temperature variability

2019 ◽  
Vol 116 (18) ◽  
pp. 8728-8733 ◽  
Author(s):  
Feng Zhu ◽  
Julien Emile-Geay ◽  
Nicholas P. McKay ◽  
Gregory J. Hakim ◽  
Deborah Khider ◽  
...  
Keyword(s):  
Climate Models ◽  
Initial Conditions ◽  
Low Frequency ◽  
Deep Ocean ◽  
Critical Element ◽  
Average Temperature ◽  
Global Mean Temperature ◽  
Low Frequency Variability ◽  
Climate Forcings ◽  
Global Mean

Climate records exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It is unclear whether climate models are capable of simulating these fluctuations, which draws into question their ability to simulate such variability in the coming decades and centuries. Using the latest simulations and data syntheses, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multimillennial. Our results confirm the existence of a scaling break between orbital and annual peaks, occurring around millennial periodicities. That both simple and comprehensive ocean–atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. This result implies that Holocene low-frequency variability is partly a consequence of the climate system’s integrated memory of orbital forcing. We conclude that climate models appear to contain the essential physics to correctly simulate the spectral continuum of global-mean temperature; however, regional discrepancies remain unresolved. A critical element of successfully simulating suborbital climate variability involves, we hypothesize, initial conditions of the deep ocean state that are consistent with observations of the recent past.

scholarly journals The Effect of a Well-Resolved Stratosphere on Surface Climate: Differences between CMIP5 Simulations with High and Low Top Versions of the Met Office Climate Model

2012 ◽  
Vol 25 (20) ◽  
pp. 7083-7099 ◽  
Author(s):  
S. C. Hardiman ◽  
N. Butchart ◽  
T. J. Hinton ◽  
S. M. Osprey ◽  
L. J. Gray
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Circulation Model ◽  
Climate Simulation ◽  
Reanalysis Dataset ◽  
Quasi Biennial Oscillation ◽  
Surface Climate ◽  
The Impact

Abstract The importance of using a general circulation model that includes a well-resolved stratosphere for climate simulations, and particularly the influence this has on surface climate, is investigated. High top model simulations are run with the Met Office Unified Model for the Coupled Model Intercomparison Project Phase 5 (CMIP5). These simulations are compared to equivalent simulations run using a low top model differing only in vertical extent and vertical resolution above 15 km. The period 1960–2002 is analyzed and compared to observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Long-term climatology, variability, and trends in surface temperature and sea ice, along with the variability of the annular mode index, are found to be insensitive to the addition of a well-resolved stratosphere. The inclusion of a well-resolved stratosphere, however, does improve the impact of atmospheric teleconnections on surface climate, in particular the response to El Niño–Southern Oscillation, the quasi-biennial oscillation, and midwinter stratospheric sudden warmings (i.e., zonal mean wind reversals in the middle stratosphere). Thus, including a well-represented stratosphere could improve climate simulation on intraseasonal to interannual time scales.

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