scholarly journals Long Time-Scale Teleconnection Patterns in the Northern Atlantic and Pacific

2012 ◽  
Vol 25 (1) ◽  
pp. 414-422
Author(s):  
George J. Boer
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Potential Predictability ◽  
Teleconnection Patterns ◽  
Statistical Robustness ◽  
Model Control ◽  
Long Time ◽  
Total Variability ◽  
Northern Atlantic ◽  
Hadley Centre

Abstract Long time-scale teleconnection patterns, with common features in both the northern Atlantic and Pacific regions, are identified. The teleconnection patterns arise in an investigation of the internally generated variability in a multimodel ensemble of coupled climate model control simulations. The large amount of data involved offers statistical robustness and the benefits of combining results across models. Maxima of decadal potential predictability identify regions where long time-scale variability is an appreciable fraction of the total variability and serve as index regions for the teleconnection analysis. Annual, 5-yr, and decadal mean temperatures over these Atlantic and Pacific index regions are correlated with corresponding temperatures and precipitation rates over the globe. The resulting teleconnection patterns are reasonably similar despite the different long time-scale variability mechanisms thought to exist in the two ocean basins. Although lacking statistical robustness, some aspects of the temperature teleconnection patterns are obtained based on the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset. The similarity of the teleconnection patterns in the two northern ocean regions suggests that common variability mechanisms may be involved.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

scholarly journals Linking ITCZ Migrations to the AMOC and North Atlantic/Pacific SST Decadal Variability

2020 ◽  
Vol 33 (3) ◽  
pp. 893-905 ◽  
Author(s):  
E. Moreno-Chamarro ◽  
J. Marshall ◽  
T. L. Delworth
Keyword(s):  
Heat Transport ◽  
Time Scales ◽  
North Atlantic ◽  
Time Scale ◽  
Climate Model ◽  
Decadal Variability ◽  
Meridional Overturning Circulation ◽  
The North ◽  
Long Time ◽  
Underlying Mechanisms

AbstractWe examine the link between migrations in the intertropical convergence zone (ITCZ) and changes in the Atlantic meridional overturning circulation (AMOC), Atlantic multidecadal variability (AMV), and Pacific decadal oscillation (PDO). We use a coupled climate model that allows us to integrate over climate noise and assess underlying mechanisms. We use an ensemble of ten 300-yr-long simulations forced by a 50-yr oscillatory North Atlantic Oscillation (NAO)-derived surface heat flux anomaly in the North Atlantic, and a 4000-yr-long preindustrial control simulation performed with GFDL CM2.1. In both setups, an AMV phase change induced by a change in the AMOC’s cross-equatorial heat transport forces an atmospheric interhemispheric energy imbalance that is compensated by a change in the cross-equatorial atmospheric heat transport due to a meridional ITCZ shift. Such linkages occur on decadal time scales in the ensemble driven by the imposed forcing, and internally on multicentennial time scales in the control. Regional precipitation anomalies differ between the ensemble and the control for a zonally averaged ITCZ shift of similar magnitude, which suggests a dependence on time scale. Our study supports observational evidence of an AMV–ITCZ link in the twentieth century and further links it to the AMOC, whose long-time-scale variability can influence the phasing of ITCZ migrations. In contrast to the AMV, our calculations suggest that the PDO does not drive ITCZ migrations, because the PDO does not modulate the interhemispheric energy balance.

scholarly journals Changes in Interannual Variability and Decadal Potential Predictability under Global Warming

2009 ◽  
Vol 22 (11) ◽  
pp. 3098-3109 ◽  
Author(s):  
G. J. Boer
Keyword(s):  
Global Warming ◽  
Standard Deviation ◽  
Time Scale ◽  
Climate Model ◽  
Decadal Variability ◽  
Climate Change Scenarios ◽  
Potential Predictability ◽  
Temperature And Precipitation ◽  
Mean Temperature ◽  
The Tropics

Abstract Global warming will result in changes in mean temperature and precipitation distributions and is also expected to affect interannual and longer time-scale internally generated variability as a consequence of changes in climate processes and feedbacks. Multimodel estimates of changes in the variability of annual mean temperature and precipitation and in the variability of decadal potential predictability are investigated based on the collection of coupled climate model simulations in the Coupled Model Intercomparison Project phase 3 (CMIP3) data archive. Pooled, multimodel standard deviations of annual mean temperature and precipitation for the unforced preindustrial control climates of the models show good resemblance to observation-based estimates. The internally generated variability of the unforced climate is compared with that of the warmer conditions for simulations with the B1 and A1B climate change scenarios with forcing stabilized at year 2100 values. The standard deviation of annual mean temperature generally decreases with global warming at extratropical latitudes, with the largest percentage decreases over the oceans and largest percentage increases in the tropics and subtropics, although the magnitudes of these increases are smaller. The standard deviation of annual mean precipitation increases almost everywhere, with larger increases in the tropics. Changes are generally larger for the more strongly forced, warmer A1B scenario than for the B1 scenario. The characterization of decadal variability changes in terms of potential predictability stems from the growing interest in producing forecasts for the next decade or several decades. The potential predictability identifies that fraction of the long time-scale variability that is, at least potentially and with enough information, predictable on decadal time scales. There is a general decrease in the internally generated decadal variability of temperature and its potential predictability in the warmer world. The decrease tends to be largest where the decadal potential predictability of the unforced control climate is largest over the high-latitude oceans. The potential predictability of precipitation is small to begin with and generally decreases further. Therefore, there is a potential decrease in the decadal potential predictability of the internally generated component in a warmer world.

scholarly journals Long-Time-Scale Magnetization Ordering Induced by an Adsorbed Chiral Monolayer on Ferromagnets

ACS Nano ◽  
2021 ◽  
Author(s):  
I. Meirzada ◽  
N. Sukenik ◽  
G. Haim ◽  
S. Yochelis ◽  
L. T. Baczewski ◽  
...  
Keyword(s):  
Time Scale ◽  
Long Time

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

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