Interdecadal changes in the interannual variability of the summer temperature over Northeast Asia

2021 ◽  
pp. 1-50
Author(s):  
Ruidan Chen ◽  
Zhiping Wen ◽  
Riyu Lu ◽  
Wenjun Liu
Keyword(s):  
Interannual Variability ◽  
Northeast Asia ◽  
Tropical Indian Ocean ◽  
Summer Temperature ◽  
Atmospheric Variability ◽  
The Pacific ◽  
The Mean ◽  
Southeastern Tropical Indian Ocean ◽  
Interdecadal Changes ◽  
Mean State

AbstractThis study reveals the interdecadal changes in the interannual variability of the summer temperature over Northeast Asia (NEA), which presents an enhancement around the early 1990s and a reduction after the mid-2000s. The stronger NEA temperature variability after the early 1990s is favored by the enhanced influence of the Pacific–Japan (PJ) teleconnection, which is remotely modulated by the southeastern tropical Indian Ocean (SETIO). After the early 1990s, the mean state over the SETIO presents relatively warmer SST and ascending motion, favoring a good relationship between the local SST and convection. Therefore, the SETIO SST could prominently influence the local convection and subsequently modulate the convection over the western North Pacific (WNP) via a cross-equatorial overturning circulation. The abnormal convection over the WNP further triggers the PJ teleconnection to influence NEA. However, these ocean–atmosphere processes disappear before the early 1990s. In this period, the mean state over the SETIO features relatively colder SST and subsiding motion, accompanied by a poor relationship between the local SST and convection. Therefore, the variability of convection over the SETIO is weak, thus the atmospheric variability over the WNP is also weakened and the PJ teleconnection presents a different distribution that could not influence NEA. The reduced variability of NEA temperature after the mid-2000s is related to the feeble influence of the PJ teleconnection and the reduced variability of the SETIO SST, which is modulated by the SST over the tropical central–eastern Pacific during the preceding winter to spring.

The Role of the Indonesian Throughflow in the Indo–Pacific Climate Variability in the GFDL Coupled Climate Model

2007 ◽  
Vol 20 (11) ◽  
pp. 2434-2451 ◽  
Author(s):  
Qian Song ◽  
Gabriel A. Vecchi ◽  
Anthony J. Rosati
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Tropical Indian Ocean ◽  
Tropical Pacific ◽  
Equatorial Pacific ◽  
Indonesian Throughflow ◽  
Enso Events ◽  
State Changes ◽  
The Mean ◽  
Mean State

Abstract The impacts of the Indonesian Throughflow (ITF) on the tropical Indo–Pacific climate, particularly on the character of interannual variability, are explored using a coupled general circulation model (CGCM). A pair of CGCM experiments—a control experiment with an open ITF and a perturbation experiment in which the ITF is artificially closed—is integrated for 200 model years, with the 1990 values of trace gases. The closure of the ITF results in changes to the mean oceanic and atmospheric conditions throughout the tropical Indo–Pacific domain as follows: surface temperatures in the eastern tropical Pacific (Indian) Ocean warm (cool), the near-equatorial Pacific (Indian) thermocline flattens (shoals), Indo–Pacific warm-pool precipitation shifts eastward, and there are relaxed trade winds over the tropical Pacific and anomalous surface easterlies over the equatorial Indian Ocean. The character of the oceanic changes is similar to that described by ocean-only model experiments, though the amplitude of many features in the tropical Indo–Pacific is amplified in the CGCM experiments. In addition to the mean-state changes, the character of tropical Indo–Pacific interannual variability is substantially modified. Interannual variability in the equatorial Pacific and the eastern tropical Indian Ocean is substantially intensified by the closure of the ITF. In addition to becoming more energetic, El Niño–Southern Oscillation (ENSO) exhibits a shorter time scale of variability and becomes more skewed toward its warm phase (stronger and more frequent warm events). The structure of warm ENSO events changes; the anomalies of sea surface temperature (SST), precipitation, and surface westerly winds are shifted to the east and the meridional extent of surface westerly anomalies is larger. In the eastern tropical Indian Ocean, the interannual SST variability off the coast of Java–Sumatra is noticeably amplified by the occurrence of much stronger cooling events. Closing the ITF shoals the eastern tropical Indian Ocean thermocline, which results in stronger cooling events through enhanced atmosphere–thermocline coupled feedbacks. Changes to the interannual variability caused by the ITF closure rectify into mean-state changes in tropical Indo–Pacific conditions. The modified Indo–Pacific interannual variability projects onto the mean-state differences between the ITF open and closed scenarios, rectifying into mean-state differences. These results suggest that CGCMs need to reasonably simulate the ITF in order to successfully represent not just the mean climate, but its variations as well.

scholarly journals Relations between Annular Modes and the Mean State: Southern Hemisphere Winter

2007 ◽  
Vol 64 (9) ◽  
pp. 3328-3339 ◽  
Author(s):  
Francis Codron
Keyword(s):  
Southern Hemisphere ◽  
Low Frequency ◽  
Stationary Waves ◽  
Annular Modes ◽  
The Pacific ◽  
Latitudinal Shift ◽  
The Indian Ocean ◽  
The Mean ◽  
Hemisphere Winter ◽  
Mean State

Abstract In a zonally symmetric climatology with a single eddy-driven jet, such as prevails in the Southern Hemisphere summer, the midlatitude variability is dominated by fluctuations of the jet around its mean position, as described by the Southern Hemisphere annular mode (SAM). To study whether this result holds for a zonally asymmetric climatology, the observed variability of the Southern Hemisphere winter is analyzed. The mean state in this case is characterized by relatively weak stationary waves; yet there exist significant zonal variations in the mean strength and meridional structure of the subtropical jet stream. As in summer, the winter SAM signature is annular in shape and the corresponding wind anomalies are dipolar; but it is associated with two different behaviors of the eddy-driven jet in different longitudinal ranges. Over the Indian Ocean, the SAM is associated primarily with a latitudinal shift of the jet around its mean position. Over the Pacific sector, it is instead characterized by a seesaw in the wind speed between two distinct latitudes, corresponding to the positions of the midlatitude and subtropical jets. Composites of eddy forcing and baroclinicity over both sectors appear consistent with the two different behaviors. As in the zonal-mean case, high-frequency eddies both force and maintain the low-frequency wind anomalies associated with the SAM. The positive feedback by eddies is, however, not local: changes in the eddy forcing are influenced most strongly by zonal wind anomalies located upstream.

scholarly journals Comparative Analysis of the Western Arctic Surface Climate among Observations and Model Simulations

2007 ◽  
Vol 11 (6) ◽  
pp. 1-24 ◽  
Author(s):  
Wanli Wu ◽  
Amanda H. Lynch ◽  
Sheldon Drobot ◽  
James Maslanik ◽  
A. David McGuire ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Sea Level ◽  
Spatial Patterns ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Surface Climate ◽  
Western Arctic ◽  
The Mean ◽  
Global Reanalysis ◽  
Mean State

Abstract Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade−1, SAT increasing 0.10°C decade−1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications.

The Seasonal Cycle of Interannual Variability and the Dynamical Imprint of the Seasonally Varying Mean State

2003 ◽  
Vol 60 (13) ◽  
pp. 1577-1592 ◽  
Author(s):  
Grant Branstator ◽  
Jorgen Frederiksen
Keyword(s):  
Interannual Variability ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Warm Season ◽  
Circulation Model ◽  
Intrinsic Variability ◽  
Linear Framework ◽  
The Mean ◽  
Barotropic Vorticity ◽  
Mean State

Abstract Various aspects of the seasonal cycle of interannual variability of the observed 300-hPa streamfunction are documented and related to dynamical influences of the seasonality of the mean circulation. The stochastically excited nondivergent barotropic vorticity equation linearized about upper-tropospheric climatological mean states from each month of the year is used to identify characteristics of interannual variability that the seasonal cycle of the mean state should modulate. The result is interannual variability with (a) extratropical centers of variance that are much stronger in winter than summer and that are confined to midlatitudes during the warm season, (b) an annual cycle of preferred scales in midlatitudes with largest scales occurring during winter and a semiannual cycle of scales in the subtropics, and (c) streamfunction tendencies from interannual fluxes that adjust to the seasonally varying climatological eddies in such a way as to damp them. Because these same properties are also shown to exist in nature, it is concluded that the linear framework is a useful means of understanding the seasonality of interannual disturbances and that seasonality of the mean state leaves a pronounced imprint on interannual variability. Analysis of an ensemble of general circulation model integrations indicates the signatures of seasonality produced in the stochastically driven linear framework are more useful for understanding intrinsic interannual variability than variability caused by seasonally varying sea surface temperature anomalies. Furthermore, it is found that the intrinsic variability of the GCM has properties very much like those in nature, another indication that organization resulting from anomalous forcing structure is not required for production of many aspects of the observed seasonality of interannual variability.

scholarly journals Interdecadal Shifts in the Winter Monsoon Rainfall of the Philippines

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 464 ◽  
Author(s):  
Lyndon M. Olaguera ◽  
Jun Matsumoto ◽  
Hisayuki Kubota ◽  
Tomoshige Inoue ◽  
Esperanza O. Cayanan ◽  
...  
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Monsoon Rainfall ◽  
El Nino ◽  
The Philippines ◽  
Winter Monsoon ◽  
Rainfall Time Series ◽  
Asian Winter Monsoon ◽  
The Pacific ◽  
The Mean

This study investigates the interdecadal shifts in the winter monsoon (November to March) rainfall of the Philippines from 1961 to 2008. Monthly analysis of the winter monsoon rainfall shows that the shifts are most remarkable during December. In particular, two interdecadal shifts are identified in the December rainfall time series around 1976/1977 and 1992/1993. To facilitate the examination of the possible mechanisms leading to these shifts, the analysis period is divided into three epochs: 1961–1976 (E1), 1977–1992 (E2), and 1993–2008 (E3). The mean and interannual variability of rainfall during E2 are suppressed compared with the two adjoining epochs. The shift around 1976/1977 is related to the phase shift of the Pacific Decadal Oscillation (PDO) from a negative phase to a positive phase and features an El Niño-like sea surface temperature (SST) change over the Pacific basin, while that around 1992/1993 is related to a La Niña-like SST change. Further analysis of the largescale circulation features shows that the decrease in the mean rainfall during E2 can be attributed to the weakening of the low-level easterly winds, decrease in moisture transport, and decrease in tropical cyclone activity. In addition, the suppressed interannual variability of rainfall during E2 can be partly attributed to the El Niño-like SST change and the weakening of the East Asian winter monsoon.

Diagnosing Northern Hemisphere Jet Portrayal in 17 CMIP3 Global Climate Models: Twentieth-Century Intermodel Variability

2013 ◽  
Vol 26 (14) ◽  
pp. 4910-4929 ◽  
Author(s):  
Sharon C. Delcambre ◽  
David J. Lorenz ◽  
Daniel J. Vimont ◽  
Jonathan E. Martin
Keyword(s):  
Twentieth Century ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Jet Stream ◽  
The Pacific ◽  
Ensemble Mean ◽  
The Mean ◽  
Upper Level ◽  
Mean State

Abstract The present study focuses on diagnosing the intermodel variability of nonzonally averaged NH winter jet stream portrayal in 17 global climate models (GCMs) from phase three of the Coupled Model Intercomparison Project (CMIP3). Relative to the reanalysis, the ensemble-mean 300-hPa Atlantic jet is too zonally extended and located too far equatorward in GCMs. The Pacific jet varies significantly between modeling groups, with large biases in the vicinity of the jet exit region that cancel in the ensemble mean. After seeking relationships between twentieth-century model wind biases and 1) the internal modes of jet variability or 2) tropical sea surface temperatures (SSTs), it is found that biases in upper-level winds are strongly related to an ENSO-like pattern in winter-mean tropical Pacific Ocean SST biases. The spatial structure of the leading modes of variability of the upper-level jet in the twentieth century is found to be accurately modeled in all 17 GCMs. Also, it is shown that Pacific model biases in the longitude of EOFs 1 and 2 are strongly linked to the modeled longitude of the Pacific jet exit, indicating that the improved characterization of the mean state of the Pacific jet may positively impact the modeled variability. This work suggests that improvements in model portrayal of the tropical Pacific mean state may significantly advance the portrayal of the mean state of the Pacific and Atlantic jets, which will consequently improve the modeled jet stream variability in the Pacific. To complement these findings, a companion paper examines the twenty-first-century GCM projections of the nonzonally averaged NH jet streams.

scholarly journals Impact of the mean state on El Niño induced western North Pacific anomalous anticyclone during its decaying summer in AMIP models

2021 ◽  
pp. 1-49
Author(s):  
Xieyuan Wang ◽  
Tim Li ◽  
Chao He
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
North Pacific ◽  
Western North Pacific ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Cp El Niño ◽  
Anomalous Anticyclone ◽  
The Mean ◽  
Mean State

AbstractThrough the diagnosis of 29 Atmospheric Model Inter-comparison Project (AMIP) experiments from the CMIP5 inter-comparison project, we investigate the impact of the mean state on simulated western North Pacific anomalous anticyclone (WNPAC) during El Niño decaying summer. The result indicates that the inter-model difference of the JJA mean precipitation in the Indo-western Pacific warm pool is responsible for the difference of the WNPAC. During the decaying summer of an Eastern Pacific (EP) type El Niño, a model that simulates excessive mean rainfall over the western North Pacific (WNP) reproduces a stronger WNPAC response, through an enhanced local convection-circulation-moisture feedback. The intensity of the simulated WNPAC during the decay summer of a Central Pacific (CP) type El Niño, on the other hand, depends on the mean precipitation over the tropical Indian Ocean. The distinctive WNPAC-mean precipitation relationships between the EP and CP El Niño result from different anomalous SST patterns in the WNP. While the local SST anomaly plays an active role in maintaining the WNPAC during the EP El Niño, it plays a passive role during the CP El Niño. As a result, only the mean-state precipitation/moisture field in the tropical Indian Ocean modulates the circulation anomaly in the WNP in the latter case.

scholarly journals A 10–15-Yr Modulation Cycle of ENSO Intensity

2009 ◽  
Vol 22 (7) ◽  
pp. 1718-1735 ◽  
Author(s):  
Fengpeng Sun ◽  
Jin-Yi Yu
Keyword(s):  
El Niño ◽  
El Nino ◽  
Surface Wind ◽  
Tropical Pacific ◽  
La Niña ◽  
Central Pacific ◽  
La Nina ◽  
The Pacific ◽  
The Mean ◽  
Mean State

Abstract This study examines the slow modulation of El Niño–Southern Oscillation (ENSO) intensity and its underlying mechanism. A 10–15-yr ENSO intensity modulation cycle is identified from historical and paleoclimate data by calculating the envelope function of boreal winter Niño-3.4 and Niño-3 sea surface temperature (SST) indices. Composite analyses reveal interesting spatial asymmetries between El Niño and La Niña events within the modulation cycle. In the enhanced intensity periods of the cycle, El Niño is located in the eastern tropical Pacific and La Niña in the central tropical Pacific. The asymmetry is reversed in the weakened intensity periods: El Niño centers in the central Pacific and La Niña in the eastern Pacific. El Niño and La Niña centered in the eastern Pacific are accompanied with basin-scale surface wind and thermocline anomalies, whereas those centered in the central Pacific are accompanied with local wind and thermocline anomalies. The El Niño–La Niña asymmetries provide a possible mechanism for ENSO to exert a nonzero residual effect that could lead to slow changes in the Pacific mean state. The mean state changes are characterized by an SST dipole pattern between the eastern and central tropical Pacific, which appears as one leading EOF mode of tropical Pacific decadal variability. The Pacific Walker circulation migrates zonally in association with this decadal mode and also changes the mean surface wind and thermocline patterns along the equator. Although the causality has not been established, it is speculated that the mean state changes in turn favor the alternative spatial patterns of El Niño and La Niña that manifest as the reversed ENSO asymmetries. Using these findings, an ENSO–Pacific climate interaction mechanism is hypothesized to explain the decadal ENSO intensity modulation cycle.

Interannual variability of the Tropical Indian Ocean mixed layer depth

2012 ◽  
Vol 40 (3-4) ◽  
pp. 743-759 ◽  
Author(s):  
M. G. Keerthi ◽  
M. Lengaigne ◽  
J. Vialard ◽  
C. de Boyer Montégut ◽  
P. M. Muraleedharan
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Indian Ocean ◽  
Ocean Mixed Layer ◽  
Layer Depth ◽  
Ocean Mixed Layer Depth
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