scholarly journals Decadal-to-Multidecadal Variability of Seasonal Land Precipitation in Northern Hemisphere in Observation and CMIP6 Historical Simulations

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 195
Author(s):  
Hua Chen ◽  
Zhenchen Xu
Keyword(s):  
Northern Hemisphere ◽  
Atlantic Multidecadal Oscillation ◽  
Ensemble Empirical Mode Decomposition ◽  
Dominant Mode ◽  
Coupled Models ◽  
Multidecadal Variability ◽  
The North ◽  
Mode Decomposition ◽  
Four Seasons ◽  
Oceanic Forcing

Based on the centennial-scale observations and CMIP6 historical simulations, this paper employs the ensemble empirical mode decomposition to extract the decadal-to-multidecadal variability of land precipitation (DMVLP) in the northern hemisphere. The spatial distributions of the dominant mode from the empirical orthogonal function are different in four seasons. Regions with the same sign of precipitation anomalies are likely to be teleconnected through oceanic forcing. The temporal evolutions of the leading modes are similar in winter and spring, with an amplitude increasing after the late 1970s, probably related to the overlap of oceanic multidecadal signals. In winter and spring, the Interdecadal Pacific Oscillation (IPO) and the Atlantic Multidecadal Oscillation (AMO) play a joint role. They were in phase before late 1970s and out of phase after then, weakening/strengthening the impacts of the North Pacific and North Atlantic on the DMVLP before/after late 1970s. In summer and autumn, AMO alone plays a part and the amplitude of time series does not vary as in winter and spring. The ability of the coupled models from CMIP6 historical simulations is also evaluated. The good-models average largely captures the spatial structure in four seasons and the associated oceanic signals. The poor-models average is hardly or weakly correlated with observation.

scholarly journals The Internal Multidecadal Variability of SST in the Pacific and Its Impact on Air Temperature and Rainfall over Land in the Northern Hemisphere

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 153
Author(s):  
Hua Chen ◽  
Donglin He ◽  
Zhiwei Zhu
Keyword(s):  
Northern Hemisphere ◽  
Air Temperature ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Ensemble Empirical Mode Decomposition ◽  
Near Surface ◽  
Multidecadal Variability ◽  
The North ◽  
Mode Decomposition ◽  
The Pacific

Based on the centennial-scale observations and re-analyses, this paper employs the ensemble empirical mode decomposition to separate the internal multidecadal variability (IMV) from the externally-forced variability of sea surface temperature (SST), and then defines new indices that represent the IMV of SST in the North Pacific (NPIMV) and South Pacific (SPIMV), respectively. The spatial structure of NPIMV/SPIMV shows remarkably positive SST anomaly only in the index-defined region; meanwhile, the temporal evolutions of NPIMV and SPIMV are uncorrelated, indicating their independence of each other. Both NPIMV and SPIMV play a critical role in the near-surface air temperature and rainfall over land in the Northern hemisphere, especially in the season when their intensity is the strongest. It is through teleconnection wave trains that NPIMV and SPIMV exert influences on remote regions. Results from another two rainfall datasets are found to be consistent in the majority of the Northern hemisphere in response to NPIMV/SPIMV, yet disagreement exists in certain regions due to large uncertainties of rainfall datasets.

scholarly journals The Impact of North Atlantic–Arctic Multidecadal Variability on Northern Hemisphere Surface Air Temperature

2010 ◽  
Vol 23 (21) ◽  
pp. 5668-5677 ◽  
Author(s):  
Vladimir A. Semenov ◽  
Mojib Latif ◽  
Dietmar Dommenget ◽  
Noel S. Keenlyside ◽  
Alexander Strehz ◽  
...  
Keyword(s):  
Climate Variability ◽  
Northern Hemisphere ◽  
North Atlantic ◽  
The Arctic ◽  
Decadal Climate Variability ◽  
Multidecadal Variability ◽  
The North ◽  
Hemisphere Surface ◽  
The North Atlantic ◽  
Decadal Climate

Abstract The twentieth-century Northern Hemisphere surface climate exhibits a long-term warming trend largely caused by anthropogenic forcing, with natural decadal climate variability superimposed on it. This study addresses the possible origin and strength of internal decadal climate variability in the Northern Hemisphere during the recent decades. The authors present results from a set of climate model simulations that suggest natural internal multidecadal climate variability in the North Atlantic–Arctic sector could have considerably contributed to the Northern Hemisphere surface warming since 1980. Although covering only a few percent of the earth’s surface, the Arctic may have provided the largest share in this. It is hypothesized that a stronger meridional overturning circulation in the Atlantic and the associated increase in northward heat transport enhanced the heat loss from the ocean to the atmosphere in the North Atlantic region and especially in the North Atlantic portion of the Arctic because of anomalously strong sea ice melt. The model results stress the potential importance of natural internal multidecadal variability originating in the North Atlantic–Arctic sector in generating interdecadal climate changes, not only on a regional scale, but also possibly on a hemispheric and even a global scale.

scholarly journals Identification of the Eurasian–North Pacific Multidecadal Oscillation and Its Relationship to the AMO

2013 ◽  
Vol 26 (20) ◽  
pp. 8139-8153 ◽  
Author(s):  
Ming-Ying Lee ◽  
Huang-Hsiung Hsu
Keyword(s):  
North Pacific ◽  
Geopotential Height ◽  
Western Europe ◽  
Atlantic Multidecadal Oscillation ◽  
Warming Trend ◽  
Multidecadal Variability ◽  
Upper Troposphere ◽  
The North ◽  
The Tropics ◽  
The North Pacific

Abstract A multidecadal geopotential height pattern in the upper troposphere of the extratropical Northern Hemisphere (NH) is identified in this study. This pattern is characterized by the nearly zonal symmetry of geopotential height and temperature between 35° and 65°N and the equivalent barotropic vertical structure with the largest amplitude in the upper troposphere. This pattern is named the Eurasian–Pacific multidecadal oscillation (EAPMO) to describe its multidecadal time scale and the largest amplitudes over Eurasia and the North Pacific. Although nearly extending over the entire extratropics, the EAPMO exhibits larger amplitudes over western Europe, East Asia, and the North Pacific with a zonal scale equivalent to zonal wavenumbers 4 and 5. The zonally asymmetric perturbation tends to amplify over the major mountain ranges in the region, suggesting a significant topographic influence. The EAPMO has fluctuated concurrently with the Atlantic multidecadal oscillation (AMO) at least since the beginning of the twentieth century. The numerical simulation results suggest that the EAPMO could be induced by the AMO-like sea surface temperature anomaly and strengthened regionally by topography, especially over the Asian highland region, although the amplitude was undersimulated. This study found that the multidecadal variability of the upper-tropospheric geopotential height in the extratropical NH is much more complicated than in the tropics and the Southern Hemisphere (SH). It takes both first (warming trend) and second (multidecadal) EOFs to explain the multidecadal variability in the extratropical NH, while only the first EOF, which exhibited a warming trend, is sufficient for the tropics and SH.

The Multidecadal Variability of the Asymmetric Mode of the Boreal Autumn Hadley Circulation and Its Link to the Atlantic Multidecadal Oscillation

2016 ◽  
Vol 29 (15) ◽  
pp. 5625-5641 ◽  
Author(s):  
Yipeng Guo ◽  
Jianping Li ◽  
Juan Feng ◽  
Fei Xie ◽  
Cheng Sun ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Hadley Circulation ◽  
Atlantic Multidecadal Oscillation ◽  
Meridional Wind ◽  
Vertical Shear ◽  
Asymmetric Mode ◽  
Multidecadal Variability ◽  
Four Seasons ◽  
Precipitation Difference

Abstract Previous studies show that the first principal mode of the variability of the seasonal mean Hadley circulation (HC) is an equatorial asymmetric mode (AM) with long-term trend. This study demonstrates that the variability of the boreal autumn [September–November (SON)] HC is also dominated by an AM, but with multidecadal variability. The SON AM has ascending and descending branches located at approximately 20°N and 20°S, respectively, and explains about 40% of the total variance. Further analysis reveals that the AM is closely linked to the Atlantic multidecadal oscillation (AMO), which is associated with a large cross-equatorial sea surface temperature (SST) gradient and sea level pressure (SLP) gradient. The cross-equatorial thermal contrast further induces an equatorial asymmetric HC anomaly. Numerical simulations conducted on an atmospheric general circulation model also suggest that AMO-associated SST anomalies can also induce a cross-equatorial SLP gradient and anomalous vertical shear of the meridional wind at the equator, both of which indicate asymmetric HC anomaly. Therefore, the AM of the variability of the boreal autumn HC has close links to the AMO. Further analysis demonstrates that the AMO in SON has a closer relationship with AM than those in the other seasons. A possible reason is that the AMO-associated zonal mean SST anomaly in the tropics has differences among the four seasons, which leads to different atmospheric circulation responses. The AM in SON has inversed impacts on the tropical precipitation, suggesting that the precipitation difference between the northern and southern tropics has multidecadal variability.

scholarly journals A Characterization of African Easterly Waves on 2.5–6-Day and 6–9-Day Time Scales

2013 ◽  
Vol 26 (18) ◽  
pp. 6750-6774 ◽  
Author(s):  
Man-Li C. Wu ◽  
Oreste Reale ◽  
Siegfried D. Schubert
Keyword(s):  
Time Scales ◽  
Ensemble Empirical Mode Decomposition ◽  
African Easterly Waves ◽  
Pressure System ◽  
Easterly Waves ◽  
African Easterly Jet ◽  
The North ◽  
Easterly Wave ◽  
Mode Decomposition ◽  
The Tropics

Abstract This study shows that the African easterly wave (AEW) activity over the African monsoon region and the northern tropical Atlantic can be divided in two distinct temporal bands with time scales of 2.5–6 and 6–9 days. The results are based on a two-dimensional ensemble empirical mode decomposition (2D-EEMD) of the Modern-Era Retrospective Analysis for Research and Applications (MERRA). The novel result of this investigation is that the 6–9-day waves appear to be located predominantly to the north of the African easterly jet (AEJ), originate at the jet level, and are different in scale and structure from the well-known low-level 2.5–6-day waves that develop baroclinically on the poleward flank of the AEJ. Moreover, they appear to interact with midlatitude eastward-propagating disturbances, with the strongest interaction taking place at the latitudes where the core of the Atlantic high pressure system is located. Composite analyses applied to the mode decomposition indicate that the interaction of the 6–9-day waves with midlatitude systems is characterized by enhanced southerly (northerly) flow from (toward) the tropics. This finding agrees with independent studies focused on European floods, which have noted enhanced moist transport from the ITCZ toward the Mediterranean region on time scales of about a week as important precursors of extreme precipitation.

371. The properties of New Zealand butters and butterfats I. Iodine, reichert and saponification values and softening points of monthly samples of butterfats from nine commercial factories over four years

1948 ◽  
Vol 15 (3) ◽  
pp. 377-386 ◽  
Author(s):  
G. A. Cox ◽  
F. H. McDowall
Keyword(s):  
New Zealand ◽  
Northern Hemisphere ◽  
Iodine Value ◽  
The South ◽  
Monthly Average ◽  
The North ◽  
Four Seasons ◽  
Iodine Values ◽  
The One

Iodine values, Reichert values, saponification values and softening points of butterfats from butters collected at monthly intervals over a period of 4 years from 9 factories representative of the main butter-producing districts in New Zealand were determined. The trend of variation of any one property throughout the season was remarkably uniform, both for different factories in the one season, and for any one property in the four seasons. Weighted monthly average iodine values, Reichert values, saponification values and softening points for the butterfat from all factories over 4 years were 36.7 (33.8–40.2), 30.4 (25.5–32.3), 229.5 (225.5–232.7) and 33.1 (32.2–33.7) respectively. The minimum iodine value occurred in midsummer, i.e. at the season of the year when maximum values are reported for northern hemisphere butters. The iodine values for South Island butterfats diverged markedly from those for the North Island butterfats during the winter, i.e. at the time when turnips are fed to cows in the South. In spite of these lower iodine values, the softening points of the South Island butterfats were lower throughout the year.

scholarly journals Hybrid improved empirical mode decomposition and BP neural network model for the prediction of sea surface temperature

Ocean Science ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 349-360 ◽  
Author(s):  
Zhiyuan Wu ◽  
Changbo Jiang ◽  
Mack Conde ◽  
Bin Deng ◽  
Jie Chen
Keyword(s):  
Neural Network ◽  
Empirical Mode Decomposition ◽  
Bp Neural Network ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Ensemble Empirical Mode Decomposition ◽  
The North ◽  
Mode Decomposition ◽  
Bpnn Model

Abstract. Sea surface temperature (SST) is the major factor that affects the ocean–atmosphere interaction, and in turn the accurate prediction of SST is the key to ocean dynamic prediction. In this paper, an SST-predicting method based on empirical mode decomposition (EMD) algorithms and back-propagation neural network (BPNN) is proposed. Two different EMD algorithms have been applied extensively for analyzing time-series SST data and some nonlinear stochastic signals. The ensemble empirical mode decomposition (EEMD) algorithm and complementary ensemble empirical mode decomposition (CEEMD) algorithm are two improved algorithms of EMD, which can effectively handle the mode-mixing problem and decompose the original data into more stationary signals with different frequencies. Each intrinsic mode function (IMF) has been taken as input data to the back-propagation neural network model. The final predicted SST data are obtained by aggregating the predicted data of individual series of IMFs (IMFi). A case study of the monthly mean SST anomaly (SSTA) in the northeastern region of the North Pacific shows that the proposed hybrid CEEMD-BPNN model is much more accurate than the hybrid EEMD-BPNN model, and the prediction accuracy based on a BP neural network is improved by the CEEMD method. Statistical analysis of the case study demonstrates that applying the proposed hybrid CEEMD-BPNN model is effective for the SST prediction. Highlights include the following: Highlights. An SST-predicting method based on the hybrid EMD algorithms and BP neural network method is proposed in this paper. SST prediction results based on the hybrid EEMD-BPNN and CEEMD-BPNN models are compared and discussed. A case study of SST in the North Pacific shows that the proposed hybrid CEEMD-BPNN model can effectively predict the time-series SST.

scholarly journals Ocean–Atmosphere Dynamical Coupling Fundamental to the Atlantic Multidecadal Oscillation

2018 ◽  
Vol 32 (1) ◽  
pp. 251-272 ◽  
Author(s):  
Robert C. J. Wills ◽  
Kyle C. Armour ◽  
David S. Battisti ◽  
Dennis L. Hartmann
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
Climate Models ◽  
Atlantic Multidecadal Oscillation ◽  
Heat Fluxes ◽  
Meridional Overturning Circulation ◽  
Multidecadal Variability ◽  
The North ◽  
Dynamical Coupling ◽  
The North Atlantic

Abstract The North Atlantic has shown large multidecadal temperature shifts during the twentieth century. There is ongoing debate about whether this variability arises primarily through the influence of atmospheric internal variability, through changes in ocean circulation, or as a response to anthropogenic forcing. This study isolates the mechanisms driving Atlantic sea surface temperature variability on multidecadal time scales by using low-frequency component analysis (LFCA) to separate the influences of high-frequency variability, multidecadal variability, and long-term global warming. This analysis objectively identifies the North Atlantic subpolar gyre as the dominant region of Atlantic multidecadal variability. In unforced control runs of coupled climate models, warm subpolar temperatures are associated with a strengthened Atlantic meridional overturning circulation (AMOC) and anomalous local heat fluxes from the ocean into the atmosphere. Atmospheric variability plays a role in the intensification and subsequent weakening of ocean overturning and helps to communicate warming into the tropical Atlantic. These findings suggest that dynamical coupling between atmospheric and oceanic circulations is fundamental to the Atlantic multidecadal oscillation (AMO) and motivate approaching decadal prediction with a focus on ocean circulation.

A stochastic dynamical systems view of the Atlantic Multidecadal Oscillation

2008 ◽  
Vol 366 (1875) ◽  
pp. 2543-2558 ◽  
Author(s):  
H.A Dijkstra ◽  
L.M Frankcombe ◽  
A.S von der Heydt
Keyword(s):  
Hopf Bifurcation ◽  
Dynamical Systems ◽  
Normal Mode ◽  
Ocean Circulation ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Equation Model ◽  
Stochastic Dynamical Systems ◽  
Multidecadal Variability ◽  
The North

We provide a dynamical systems framework to understand the Atlantic Multidecadal Oscillation and show that this framework is in many ways similar to that of the El Niño/Southern Oscillation. A so-called minimal primitive equation model is used to represent the Atlantic Ocean circulation. Within this minimal model, we identify a normal mode of multidecadal variability that can destabilize the background climate state through a Hopf bifurcation. Next, we argue that noise is setting the amplitude of the sea surface temperature variability associated with this normal mode. The results provide support that a stochastic Hopf bifurcation is involved in the multidecadal variability as observed in the North Atlantic.

scholarly journals Prediction of North Atlantic Oscillation Index with Convolutional LSTM Based on Ensemble Empirical Mode Decomposition

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 252 ◽  
Author(s):  
Shijin Yuan ◽  
Xiaodan Luo ◽  
Bin Mu ◽  
Jing Li ◽  
Guokun Dai
Keyword(s):  
North Atlantic Oscillation ◽  
Empirical Mode Decomposition ◽  
North Atlantic ◽  
Ensemble Empirical Mode Decomposition ◽  
Machine Learning Algorithms ◽  
Index Data ◽  
The North ◽  
Nao Index ◽  
Mode Decomposition ◽  
The North Atlantic

The North Atlantic Oscillation (NAO) is the most significant mode of the atmosphere in the North Atlantic, and it plays an important role in regulating the local weather and climate and even those of the entire Northern Hemisphere. Therefore, it is vital to predict NAO events. Since the NAO event can be quantified by the NAO index, an effective neural network model EEMD-ConvLSTM, which is based on Convolutional Long Short-Term Memory (ConvLSTM) with Ensemble Empirical Mode Decomposition (EEMD), is proposed for NAO index prediction in this paper. EEMD is applied to preprocess NAO index data, which are issued by the National Oceanic and Atmospheric Administration (NOAA), and NAO index data are decomposed into several Intrinsic Mode Functions (IMFs). After being filtered by the energy threshold, the remaining IMFs are used to reconstruct new NAO index data as the input of ConvLSTM. In order to evaluate the performance of EEMD-ConvLSTM, six methods were selected as the benchmark, which included traditional models, machine learning algorithms, and other deep neural networks. Furthermore, we forecast the NAO index with EEMD-ConvLSTM and the Rolling Forecast (RF) and compared the results with those of Global Forecast System (GFS) and the averaging of 11 Medium Range Forecast (MRF) model ensemble members (ENSM) provided by the NOAA Climate Prediction Center. The experimental results show that EEMD-ConvLSTM not only has the highest reliability from evaluation metrics, but also can better capture the variation trend of the NAO index data.

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