scholarly journals Impact of October Snow Cover in Central Siberia on the Following Spring Extreme Precipitation Frequency in Southern China

2021 ◽  
Vol 9 ◽  
Author(s):  
Mengqi Zhang ◽  
Jianqi Sun
Keyword(s):  
Snow Cover ◽  
Extreme Precipitation ◽  
Southern China ◽  
Polar Vortex ◽  
Planetary Waves ◽  
Northern Eurasia ◽  
Precipitation Frequency ◽  
Stratospheric Polar Vortex ◽  
Central Siberia ◽  
Vertical Propagation

Spring extreme precipitation poses great challenges to agricultural production and economic development in southern China. From the perspective of prediction, the relationship between spring extreme precipitation frequency (SEPF) in southern China and preceding autumn snow cover over Eurasia is investigated. The results indicate that the southern China SEPF is significantly correlated with October snow cover in central Siberia. Corresponding to reduced October snow cover, the vertical propagation of planetary waves is suppressed, which leads to a strengthened stratospheric polar vortex from October to following December. The signal of the anomalous stratospheric polar vortex propagates downward to the surface, contributing to a positive North Atlantic Oscillation (NAO)-like pattern in December. The southwesterlies in the northern Eurasia-eastern Arctic associated with the positive NAO induce sea ice loss in the Barents–Kara seas in January–February, which then tends to enhance the vertical propagation of planetary waves by constructively interfering with the climatological wavenumber-1 component. Therefore, the stratosphere polar vortex is significantly weakened in spring, which further contributes to a negative Arctic Oscillation (AO)-like pattern in the troposphere. The negative spring AO is related to an anomalous cyclone in East Asia, which induces upward motion and moisture convergence in southern China, consequently providing favorable dynamic and moisture conditions for extreme precipitation in the region. The snow cover signal in central Siberia in the preceding October provides a potential source for the prediction of spring extreme precipitation variability in southern China with two seasons in advance.

Longitudinal peculiarities of planetary waves-zonal flow interaction and its role in stratosphere-troposphere dynamical coupling

2021 ◽  
Author(s):  
Wei Ke ◽  
Wen Chen ◽  
Pavel Vargin
Keyword(s):  
Wave Train ◽  
Polar Vortex ◽  
Planetary Waves ◽  
Northern Eurasia ◽  
Late Winter ◽  
Early Winter ◽  
Eastern United States ◽  
Stratospheric Polar Vortex ◽  
Downward Flux ◽  
Wave Flux

Abstract The three-dimensional (3D) planetary wave analysis provides more regionalized information on stratospheric-tropospheric dynamic interactions. The upward wave flux from the troposphere to the stratosphere is maximized above north-eastern Eurasia, while the downward flux is mainly over the North America and North Atlantic (NANA) region, which is much stronger in mid and late winter. This distribution is determined by the wave-wave interaction between the different wavenumbers of planetary waves, especially between wavenumber 1 and wavenumber 2. The upward wave flux anomalies in early winter are negatively correlated with the strength of the stratospheric polar vortex (SPV). In the mid and late winter months, the strength of the SPV is positively correlated with the first mode of 3D wave flux and has a leading relationship of approximately one month. The stronger SPV corresponds to a stronger upward wave flux above northern Eurasia and stronger downward flux over the NANA region. The interannual variation in wave flux in early winter is closely associated with the Scandinavian wave train pattern. In contrast, the wave flux variation is related to the circulation anomaly corresponding to Arctic Oscillation in mid and late winter, which causes climate anomalies across the Northern Hemisphere, especially coherent temperature changes in northern Europe, eastern United States and northeastern China.

scholarly journals Eurasian Cold Air Outbreaks under Different Arctic Stratospheric Polar Vortex Strengths

2019 ◽  
Vol 76 (5) ◽  
pp. 1245-1264 ◽  
Author(s):  
Jinlong Huang ◽  
Wenshou Tian
Keyword(s):  
Climate Models ◽  
Sensible Heat Flux ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Polar Vortex ◽  
Northern Eurasia ◽  
Reanalysis Dataset ◽  
Stratospheric Polar Vortex ◽  
Cold Air ◽  
Cold Air Outbreaks

Abstract This study analyzes the differences and similarities of Eurasian cold air outbreaks (CAOs) under the weak (CAOW), strong (CAOS), and neutral (CAON) stratospheric polar vortex states and examines the potential links between the polar vortex and Eurasian CAOs. The results indicate that the colder surface air temperature (SAT) over Europe in the earlier stages of CAOW events is likely because the amplitude of the preexisting negative North Atlantic Oscillation pattern is larger in CAOW events than in CAON and CAOS events. Marked by the considerably negative stratospheric Arctic Oscillation signals entering the troposphere, the SAT at midlatitudes over eastern Eurasia in CAOW events is colder than in CAON events. A larger diabatic heating rate related to a positive sensible heat flux anomaly in CAOW events likely offsets, to some degree, the cooling effect caused by the stronger cold advection and makes the differences in area-averaged SAT anomalies over northern Eurasia between the CAOW and CAON events look insignificant in most stages. Massive anomalous waves from the low-latitude western Pacific merge over northeastern Eurasia, then weaken the westerly wind over this region to create favorable conditions for southward advection of cold air masses in the earlier stages of all three types of CAOs. This study further analyzes the interannual relationship between the stratospheric polar vortex strength and the intensity of Eurasian CAOs and finds that climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) relative to the reanalysis dataset tend to underestimate the correlation between them. The relationship between them is strengthening under representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) scenarios over the period 2006–60. In addition, the intensity of Eurasian CAOs exhibits a decreasing trend in the past and in the future.

scholarly journals Anomalous quasi-stationary planetary waves over the Antarctic region in 1988 and 2002

2008 ◽  
Vol 26 (5) ◽  
pp. 1101-1108 ◽  
Author(s):  
A. V. Grytsai ◽  
O. M. Evtushevsky ◽  
G. P. Milinevsky
Keyword(s):  
Lower Stratosphere ◽  
Polar Vortex ◽  
Amplitude Distribution ◽  
Stationary Wave ◽  
Planetary Waves ◽  
Late Winter ◽  
Stratospheric Polar Vortex ◽  
Latitudinal Position ◽  
The Antarctic ◽  
Peak Value

Abstract. Anomalies in the Antarctic total ozone and amplitudes of the quasi-stationary planetary waves in the lower stratosphere temperature during the winter and spring of 1988 and 2002 have been compared. Westward displacement of the quasi-stationary wave (QSW) extremes by 50°–70° relative to the preceding years of the strong stratospheric polar vortex in 1987 and 2001, respectively, was observed. A dependence of the quasi-stationary wave ridge and trough positions on the strength of the westerly zonal wind in the lower stratosphere is shown. Comparison of the QSW amplitude in the lower stratosphere temperature in July and August shows that the amplitude distribution with latitude in August could be considered as a possible indication of the future anomalous warming in Antarctic spring. In August 2002, the QSW amplitude of 10 K at the edge region of the polar vortex (60° S–65° S) preceded the major warming in September, whereas in August 1988, the highest 7 K amplitude at 55° S preceded the large warming in the next months. These results suggest that the peak value of the lower stratosphere temperature QSW amplitude and the peak latitudinal position in late winter can influence the southern polar vortex strength in spring.

scholarly journals Seasonal Prediction Skill of Northern Extratropical Surface Temperature Driven by the Stratosphere

2017 ◽  
Vol 30 (12) ◽  
pp. 4463-4475 ◽  
Author(s):  
Liwei Jia ◽  
Xiaosong Yang ◽  
Gabriel Vecchi ◽  
Richard Gudgel ◽  
Thomas Delworth ◽  
...  
Keyword(s):  
Climate Model ◽  
Lower Troposphere ◽  
Polar Vortex ◽  
Seasonal Prediction ◽  
The Arctic ◽  
Northern Eurasia ◽  
Stratospheric Polar Vortex ◽  
Near Surface ◽  
Predictive Skill

This study explores the role of the stratosphere as a source of seasonal predictability of surface climate over Northern Hemisphere extratropics both in the observations and climate model predictions. A suite of numerical experiments, including climate simulations and retrospective forecasts, are set up to isolate the role of the stratosphere in seasonal predictive skill of extratropical near-surface land temperature. It is shown that most of the lead-0-month spring predictive skill of land temperature over extratropics, particularly over northern Eurasia, stems from stratospheric initialization. It is further revealed that this predictive skill of extratropical land temperature arises from skillful prediction of the Arctic Oscillation (AO). The dynamical connection between the stratosphere and troposphere is also demonstrated by the significant correlation between the stratospheric polar vortex and sea level pressure anomalies, as well as the migration of the stratospheric zonal wind anomalies to the lower troposphere.

scholarly journals Strengthened Impacts of November Snow Cover Over Siberia on the Out-of-phase Change in the Siberian High Between December and January Since 2000 and Implication for Intraseasonal Climate Prediction

2021 ◽  
Vol 9 ◽  
Author(s):  
Hongqing Yang ◽  
Ke Fan
Keyword(s):  
Phase Change ◽  
Snow Cover ◽  
Polar Vortex ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Mean Flow ◽  
Stratospheric Polar Vortex ◽  
Siberian High ◽  
Arctic Sea ◽  
Reversal Frequency

This study investigates the out-of-phase change in the Siberian High (SH) between December and January (stronger than normal in December and weaker than normal in January, and vice versa). The results show that the monthly reversal frequency of the SH between December and January increases significantly after 2000 from 30% (1981–2000) to 63% (2001-2019). Correspondingly, the influence of November snow cover over Siberia on the phase reversal of the SH has intensified after 2000. The reasons may be as follows. Higher snow depth over Siberia (SSD) in November corresponds to stronger diabatic cooling and increased snow accumulation over Siberia in November and December, which may strengthen the SH in December via the positive feedback of snow albedo. The dynamic mechanisms between the higher SSD in November and weaker SH in January are further investigated from the perspective of troposphere–stratosphere interaction. Such anomalously higher SSD with strong upward heat flux induces the upward-propagating wave activity flux in November and December over the Urals and Siberia, leading to a weaker and warmer stratospheric polar vortex in January. Subsequently, the anomalies of the stratospheric polar vortex signal propagate downwards, giving rise to a negative Arctic Oscillation–like structure in the troposphere and a weakening of the SH in January. This mechanism can be partly reproduced in CMIP6. Additionally, the variability of the September–October Arctic sea ice mainly leads to coherent variations of the SH in December and January via the eddy–mean flow interaction before 2000. Furthermore, the preceding November snow cover over Siberia enhances the intraseasonal prediction skill for the winter SH after 2000. Meanwhile, considering the previous November SSD, the prediction accuracy for the out-of-phase change in the SH between December and January increases from 16% (outputs of the NCEP’s Climate Forecast System, version 2) to 75%.

scholarly journals Eurasian autumn snow impact on winter North Atlantic Oscillation depends on cryospheric variability

2019 ◽  
Author(s):  
Martin Wegmann ◽  
Marco Rohrer ◽  
María Santolaria-Otín ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
North Atlantic Oscillation ◽  
Snow Cover ◽  
North Atlantic ◽  
Polar Vortex ◽  
Negative Temperature ◽  
Atmospheric Conditions ◽  
Sea Ice Concentration ◽  
Stratospheric Polar Vortex ◽  
Winter Climate

Abstract. In recent years, many components of the connection between Eurasian autumn snow cover and wintertime North Atlantic Oscillation (NAO) were investigated, suggesting that November snow cover distribution has strong prediction power for the upcoming Northern Hemisphere winter climate. However, non-stationarity of this relationship could impact its use for prediction routines. Here we use snow products from long-term reanalyses to investigate interannual and interdecadal links between autumnal snow cover and atmospheric conditions in winter. We find evidence for a negative NAO tendency after November with a strong west-to-east snow cover gradient, which is valid throughout the last 150 years. This correlation is linked with a consistent impact of November snow on a slowed stratospheric polar vortex. Nevertheless, interdecadal variability for this relationship shows episodes of decreased correlation power, which co-occur with episodes of low variability in the November snow index. We find that the same is also true for sea ice as an NAO predictor. The snow dipole itself is associated with reduced Barents-Kara sea ice concentration, increased Ural blocking frequency and negative temperature anomalies in eastern Eurasia. Increased sea ice variability in recent years is linked to increased snow variability, thus increasing its power in predicting the winter NAO.

scholarly journals A Simple Kinematic Model for the Lagrangian Description of Relevant Nonlinear Processes in the Stratospheric Polar Vortex

2016 ◽  
Author(s):  
Victor José García-Garrido ◽  
Jezabel Curbelo ◽  
Carlos Roberto Mechoso ◽  
Ana María Mancho ◽  
Stephen Wiggins
Keyword(s):  
Kinematic Model ◽  
Polar Vortex ◽  
Reanalysis Data ◽  
Planetary Waves ◽  
Lagrangian Description ◽  
Lagrangian Analysis ◽  
Mixing Processes ◽  
Geometrical Structures ◽  
Stratospheric Polar Vortex ◽  
Fourier Decomposition

Abstract. In this work we study the Lagrangian footprint of the planetary waves present in the Southern Hemisphere stratosphere during the Sudden Stratospheric Warming event that took place during September 2002. The Lagrangian analysis of the transport and mixing processes is carried out in the framework of dynamical systems theory, by means of a Lagrangian descriptor. We seek to describe the Lagrangian skeleton of geometrical structures that lead to filamentation phenomena and the breakdown of the polar vortex, and establish its relation with how planetary waves interact. Our approach is based on the construction of a simple kinematic model, inspired by the Fourier decomposition of the geopotential field. We show that this model is capable of reproducing the key Lagrangian features present on the reanalysis data such as the formation of filaments eroding the stratospheric polar vortex and the breakdown of the vortex.

scholarly journals Zonal wave numbers 1-5 in planetary waves from the TOMS total ozone at 65° S

2005 ◽  
Vol 23 (5) ◽  
pp. 1565-1573 ◽  
Author(s):  
A. Grytsai ◽  
Z. Grytsai ◽  
A. Evtushevsky ◽  
G. Milinevsky ◽  
N. Leonov
Keyword(s):  
Total Ozone ◽  
General Circulation ◽  
Middle Atmosphere ◽  
Polar Vortex ◽  
Planetary Waves ◽  
Wave Number ◽  
Stratospheric Polar Vortex ◽  
Term Change ◽  
Wave Numbers ◽  
The Difference

Abstract. Planetary waves in the total ozone at the southern latitude of 65° S are studied to obtain the main characteristics of the zonal wave numbers 1–5. The TOMS total ozone data were used to analyze the amplitude and periodicity variations of the five spectral components during August-December of 1979–2003. A presence of the shorter period of waves 1–3 in 1996 (7 days) in comparison with 2002 (8–12 days) is revealed which can be attributed to the distinction in conditions of typical and anomalously weak stratospheric polar vortex, probably, a strong and weak mean zonal wind. The interannual variations of the monthly and 5-month mean amplitudes of the zonal wave numbers 1–5 are described. Wave 1 has the largest amplitude in October (up to 139 DU in 2000) and increasing amplitude trend (15 DU/decade for October 1979–2003). The 5-month mean amplitudes averaged over 1979–2003 are 53.6, 29.9, 15.5, 10.5, and 7.8 DU for the wave number sequence 1, 2, 3, 4 and 5, respectively. For the stationary components the amplitudes are 38.3, 4.8, 1.8, 1.2, 0.7 DU, respectively. Thus, the stationary component of wave 1 and the traveling one of waves 2–5 are predominant. The tendencies in a long-term change in the wave number amplitude can be explained by taking into account the degree of wave deformation of the stratospheric polar vortex edge, net meridional displacements of the lower stratosphere air, and the difference between the total ozone loss and negative trends in the polar and mid-latitude regions. Keywords. General circulation – Middle atmosphere dynamics – Waves and tides

Network-based forecasting of climate phenomena

2021 ◽  
Vol 118 (47) ◽  
pp. e1922872118
Author(s):  
Josef Ludescher ◽  
Maria Martin ◽  
Niklas Boers ◽  
Armin Bunde ◽  
Catrin Ciemer ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Predictive Power ◽  
Polar Vortex ◽  
Extreme Rainfall ◽  
Systems Science ◽  
Northern Eurasia ◽  
Stratospheric Polar Vortex ◽  
Societal Challenges ◽  
Impact Phenomena ◽  
Complex Systems Science

Network theory, as emerging from complex systems science, can provide critical predictive power for mitigating the global warming crisis and other societal challenges. Here we discuss the main differences of this approach to classical numerical modeling and highlight several cases where the network approach substantially improved the prediction of high-impact phenomena: 1) El Niño events, 2) droughts in the central Amazon, 3) extreme rainfall in the eastern Central Andes, 4) the Indian summer monsoon, and 5) extreme stratospheric polar vortex states that influence the occurrence of wintertime cold spells in northern Eurasia. In this perspective, we argue that network-based approaches can gainfully complement numerical modeling.

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