scholarly journals Atmospheric Stability in a Generalized Barotropic Model

2005 ◽  
Vol 62 (2) ◽  
pp. 476-491 ◽  
Author(s):  
Christos M. Mitas ◽  
Walter A. Robinson
Keyword(s):  
Quantitative Description ◽  
Atmospheric Stability ◽  
Low Frequency ◽  
Initial Value ◽  
Modified Model ◽  
Barotropic Model ◽  
Upper Troposphere ◽  
Low Frequency Variability ◽  
Short Times ◽  
Better Than

Abstract An empirical modification of conventional barotropic dynamics is implemented to study the low-frequency variability (LFV) of the upper troposphere. Using the conservation of potential vorticity, generalized spectral barotropic operators that apply at single isentropic levels are constructed. In initial value calculations the empirical model shows improvement in skill compared to the conventional barotropic model, but it does not do significantly better than persistence. For short times, however, the empirically modified model shows a much closer resemblance to the observed streamfunction tendency. Overall, it is a significantly more accurate representation of the atmosphere than the conventional barotropic model. Normal, optimal, and singular modes of the modified model are calculated. The modes of the empirically modified model are more stable and more difficult to excite than those of the barotropic model. These results are consistent with previous studies that found barotropic dynamics deficient for the quantitative description of LFV. The singular modes of the modified operator have very similar patterns but explain less variance than those of the barotropic operator, which is consistent with the difficulty in detecting optimal patterns in observations. The modified barotropic operator is also more normal than the barotropic operator, and thus less variable.

Impact of the Pacific mean SST bias to the Atlantic-Pacific teleconnection

2020 ◽  
Author(s):  
Chen Li ◽  
Dietmar Dommenget ◽  
Shayne McGregor
Keyword(s):  
Decadal Variability ◽  
Atmospheric Stability ◽  
Low Frequency ◽  
Trade Wind ◽  
Atmospheric Teleconnection ◽  
Surface Warming ◽  
Sst Bias ◽  
Pacific Decadal Variability ◽  
The Pacific ◽  
Low Frequency Variability

<p><span>A robust eastern tropical Pacific surface temperature cooling trend along with the strengthening of Pacific trade wind is evident across different observations since late 1990s, which is considered as a pronounced contributor to the slowdown in global surface warming. However, most CMIP5 historical simulations failed to reproduce this La Ni</span>ñ<span>a-like change. Previous studies have attributed this discrepancy between the multi-model simulations and the observations to the underrepresentation of Pacific low-frequency variability together with the misrepresentation of inter-basin forcing response. The underlying reasons remain unclear. Here, we investigate a hypothesis that common Pacific mean SST bias may diminish the Pacific-Atlantic atmospheric teleconnection and further contribute to the underestimated eastern Pacific cooling. Model results suggest that the CMIP5-like Pacific bias acts to reduce the Atlantic heating response by strengthening the atmospheric stability over the Atlantic region and therefore weaken the trans-basin variability. In addition, </span>the Pacific bias simulation with a strong SST cold tongue substantially undermined the positive zonal wind feedback, which also contributes to the underestimated Pacific cooling response. Future efforts aim at reducing the model mean state biases may significantly help to improve the simulation skills of the trans-basin teleconnection, Pacific decadal variability, and the associated Pacific dynamics.      </p>

scholarly journals Low-Order Stochastic Mode Reduction for a Realistic Barotropic Model Climate

2005 ◽  
Vol 62 (6) ◽  
pp. 1722-1745 ◽  
Author(s):  
Christian Franzke ◽  
Andrew J. Majda ◽  
Eric Vanden-Eijnden
Keyword(s):  
Stochastic Models ◽  
Additive Noise ◽  
Low Frequency ◽  
Barotropic Model ◽  
Climate Modes ◽  
Low Frequency Variability ◽  
Systematic Strategy ◽  
Stochastic Mode ◽  
Correction Terms ◽  
Low Order

Abstract This study applies a systematic strategy for stochastic modeling of atmospheric low-frequency variability to a realistic barotropic model climate. This barotropic model climate has reasonable approximations of the Arctic Oscillation (AO) and Pacific/North America (PNA) teleconnections as its two leading principal patterns of low-frequency variability. The systematic strategy consists first of the identification of slowly evolving climate modes and faster evolving nonclimate modes by use of an empirical orthogonal function (EOF) decomposition. The low-order stochastic climate model predicts the evolution of these climate modes a priori without any regression fitting of the resolved modes. The systematic stochastic mode reduction strategy determines all correction terms and noises with minimal regression fitting of the variances and correlation times of the unresolved modes. These correction terms and noises account for the neglected interactions between the resolved climate modes and the unresolved nonclimate modes. Low-order stochastic models with only four resolved modes capture the statistics of the original barotropic model modes quite well. A budget analysis establishes that the low-order stochastic models are dominated by linear dynamics and additive noise. The linear correction terms and the additive noise stem from the linear coupling between resolved and unresolved modes, and not from nonlinear interactions between resolved and unresolved modes as assumed in previous studies.

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.

Removing Spurious Low-Frequency Variability in Drifter Velocities

2013 ◽  
Vol 30 (2) ◽  
pp. 353-360 ◽  
Author(s):  
Rick Lumpkin ◽  
Semyon A. Grodsky ◽  
Luca Centurioni ◽  
Marie-Helene Rio ◽  
James A. Carton ◽  
...  
Keyword(s):  
Low Frequency ◽  
Original Data ◽  
Strain Sensors ◽  
Wind Forcing ◽  
Stokes Drift ◽  
Interannual Variations ◽  
Transmission Frequency ◽  
Low Frequency Variability ◽  
Frequency Variations ◽  
Drifting Buoys

Abstract Satellite-tracked drifting buoys of the Global Drifter Program have drogues, centered at 15-m depth, to minimize direct wind forcing and Stokes drift. Drogue presence has historically been determined from submergence or tether strain records. However, recent studies have revealed that a significant fraction of drifters believed to be drogued have actually lost their drogues, a problem that peaked in the mid-2000s before the majority of drifters in the global array switched from submergence to tether strain sensors. In this study, a methodology is applied to the data to automatically reanalyze drogue presence based on anomalous downwind ageostrophic motion. Results indicate that the downwind slip of undrogued drifters is approximately 50% higher than previously believed. The reanalyzed results no longer exhibit the dramatic and spurious interannual variations seen in the original data. These results, along with information from submergence/tether strain and transmission frequency variations, are now being used to conduct a systematic manual reevaluation of drogue presence for each drifter in the post-1992 dataset.

scholarly journals Empirical Mode Reduction in a Model of Extratropical Low-Frequency Variability

2006 ◽  
Vol 63 (7) ◽  
pp. 1859-1877 ◽  
Author(s):  
D. Kondrashov ◽  
S. Kravtsov ◽  
M. Ghil
Keyword(s):  
Numerical Study ◽  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
The Arctic ◽  
Reduced Model ◽  
The North ◽  
Low Frequency Variability ◽  
Intraseasonal Oscillations ◽  
The Arctic Oscillation ◽  
The North Atlantic Oscillation

Abstract This paper constructs and analyzes a reduced nonlinear stochastic model of extratropical low-frequency variability. To do so, it applies multilevel quadratic regression to the output of a long simulation of a global baroclinic, quasigeostrophic, three-level (QG3) model with topography; the model's phase space has a dimension of O(104). The reduced model has 45 variables and captures well the non-Gaussian features of the QG3 model's probability density function (PDF). In particular, the reduced model's PDF shares with the QG3 model its four anomalously persistent flow patterns, which correspond to opposite phases of the Arctic Oscillation and the North Atlantic Oscillation, as well as the Markov chain of transitions between these regimes. In addition, multichannel singular spectrum analysis identifies intraseasonal oscillations with a period of 35–37 days and of 20 days in the data generated by both the QG3 model and its low-dimensional analog. An analytical and numerical study of the reduced model starts with the fixed points and oscillatory eigenmodes of the model's deterministic part and uses systematically an increasing noise parameter to connect these with the behavior of the full, stochastically forced model version. The results of this study point to the origin of the QG3 model's multiple regimes and intraseasonal oscillations and identify the connections between the two types of behavior.

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