An Arctic‐Tibetan Connection on Subseasonal to Seasonal Time Scale

Zhang, Yang; Zou, Tao; Xue, Yongkang

doi:10.1029/2018gl081476

Cited by 39 publications

(24 citation statements)

References 53 publications

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“…This is consistent with figures 2(b) and 4, which is ascribed to the different regional snow-atmosphere coupling strengths, as well as the intrinsic memory difference of the TP and the EA snow. The elevated TP is a region of strong sensible heating [1,42] receiving the primary research focus for the Asian monsoon [37,53,54]. Our results suggest that due to the relatively shorter memory of the TP snow (figure 2(b): forced atmospheric response disappears by May; see similar discussions on the TP snow by Orsolini et al [55]), the contribution of snow DA over the TP may be limited to pre-monsoon season.…”

Section: Relative Importance Of Regional Snow Da In the Ism Forecastsupporting

confidence: 55%

Assimilating multi-satellite snow data in ungauged Eurasia improves the simulation accuracy of Asian monsoon seasonal anomalies

Lin

Yang

Wei

et al. 2020

Environ. Res. Lett.

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Properly initializing land snow conditions with multi-satellite data assimilation (DA) may help tackle the long-standing challenge of Asian monsoon seasonal forecasts. However, to what extent can snow DA help resolve the problem remains largely unexplored. Here we establish, for the first time, that improved springtime snow initializations assimilating the Moderate Spectral Imaging Satellite (MODIS) snow cover fraction and the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data can improve the simulation accuracy of Asian monsoon seasonal anomalies. Focusing on the western Tibetan Plateau (TP) and mid-to high-latitude Eurasia (EA), two regions where multi-satellite snow DA is critical, we found that DA influences the monsoon circulation at different months depending on the regional snow-atmosphere coupling strengths. For the pre-monsoon season, accurate initialization of the TP snow is key, and assimilating MODIS data slightly outperforms jointly assimilating MODIS and GRACE data. For the peak-monsoon season, accurate initialization of the EA snow is more important due to its long memory, and assimilating GRACE data brings the most pronounced gains. Among all the Asian monsoon subregions, the most robust improvement is seen over central north India, a likely result of the region's strong sensitivity to thermal forcing. While this study highlights complementary snow observations as promising new sources of the monsoon predictability, it also clarifies complexities in translating DA to useful monsoon forecast skill, which may help bridge the gap between land DA and dynamical climate forecasting studies.

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Section: Relative Importance Of Regional Snow Da In the Ism Forecastsupporting

confidence: 55%

Assimilating multi-satellite snow data in ungauged Eurasia improves the simulation accuracy of Asian monsoon seasonal anomalies

Lin

Yang

Wei

et al. 2020

Environ. Res. Lett.

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“…Yuan et al (2008) noted that the Indian Ocean dipole can affect the variation in Tibetan snow in early winter. The Arctic Oscillation (AO) can also affect the variation in snow in winter and spring via Rossby waves (Lü et al, 2008; Zhang et al, 2019). In addition, the Northern Atlantic Oscillation can strengthen the Africa‐Asian jet stream, which further favors winter snowfall over the TP (Liu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

On the Interdecadal Change in the Interannual Variation in Autumn Snow Cover Over the Central Eastern Tibetan Plateau in the Mid‐1990s

Qian

Xiao-ming

2020

JGR Atmospheres

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The interdecadal changes in the mechanisms accounting for the interannual variation in autumn snow cover over the central eastern Tibetan Plateau (TP) are investigated in this study. An autumn snow index is constructed by area averaging the snow cover over the central eastern TP. The snow index changed from a predominantly negative phase to a positive phase in 1995. Then, the data were divided into two subperiods, 1979–1994 (P1) and 1995–2017 (P2), and the differences in the mechanisms accounting for the variation in autumn snow cover were compared between P1 and P2. An analysis of the local process shows that the autumn snow cover variations over the central eastern TP are caused by snowfall from both autumn and late summer. The autumn snow cover variation over the central eastern TP imposed more significant atmospheric cooling effects during P1 than P2. During P2, except for the local process, the interannual variation in autumn snow cover in the central eastern TP is also affected by atmospheric circulation anomalies originating from the upstream North Atlantic Ocean. During P2, snow‐related North Atlantic sea surface temperature (SST) anomalies (SSTA) can induce a wave train‐like atmospheric pattern that propagates eastward across the Eurasian continent and reaches the TP. Further analysis shows that this wave train‐like atmospheric pattern over the midlatitude Eurasian continent mainly obtains energy from climatological mean flow through baroclinic energy conversion. In contrast, during P1, the North Atlantic SSTA‐related atmospheric circulation pattern tends to propagate northeastward and cannot contribute to the variation in autumn snow cover over the central eastern TP.

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“…Whether the latitudinal displacement of the jet is driven by other external forcing, e.g. Arctic forcing as shown in Overland et al (2015), Gu et al (2018) and Zhang et al (2019), or it is mostly determined by atmospheric internal dynamics is a topic that needs further investigation.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the dynamics of the interannual variabilities of the wintertime East Asian Jet Core

Chan

Zhang

et al. 2020

Clim Dyn

Self Cite

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The East Asian jet has evident interannual variability in strength and position and has broad impacts on weather and climate in the Asian-Pacific-American region. In this study, we quantify the relative contributions of distinct dynamical processes responsible for the wintertime interannual variability of the East Asian jet core. The quantification is based on analyzing the zonal momentum budgets. Our budget analyses show distinct up-and downstream controls for the interannual intensification of the jet. Over the upstream, the jet intensification is predominantly driven by enhanced upper-level angular momentum transport associated with local convective-driven Hadley-cells. In addition to convections over the Tropical Pacific, those over the Bay of Bengal-South China Sea are found responsible for a distinct local Hadley cell over 80 •-100 • E, which accelerates the jet from its very upstream. Over the downstream, angular momentum advected by the mean flow from the upstream is the first-order term responsible for the jet intensification, whereas synoptic eddies play a secondary role. For the interannual meridional displacement of the jet, synoptic eddy activities over the North Pacific are found to contribute predominantly. For both the intensification and the meridional displacement, the upper-tropospheric jet covaries closely with changes in the Subtropical Oceanic Frontal Zone in the North Pacific. Such a strong covariation implies the contributions of the air-sea interactions to the downstream jet variability.

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An Arctic‐Tibetan Connection on Subseasonal to Seasonal Time Scale

Cited by 39 publications

References 53 publications

Assimilating multi-satellite snow data in ungauged Eurasia improves the simulation accuracy of Asian monsoon seasonal anomalies

Assimilating multi-satellite snow data in ungauged Eurasia improves the simulation accuracy of Asian monsoon seasonal anomalies

On the Interdecadal Change in the Interannual Variation in Autumn Snow Cover Over the Central Eastern Tibetan Plateau in the Mid‐1990s

Quantifying the dynamics of the interannual variabilities of the wintertime East Asian Jet Core

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