Possible effect of the Tibetan Plateau on the “upstream” climate over West Asia, North Africa, South Europe and the North Atlantic

Lu, Mengmeng; Yang, Song; Li, Zhenning; He, Bian; He, Shan; Wang, Ziqian

doi:10.1007/s00382-017-3966-5

Cited by 56 publications

(73 citation statements)

References 43 publications

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“…The formation and variability of the Asian summer monsoon, in particular, is affected by the TP through thermal and mechanical effects (Wu et al, 2012(Wu et al, , 2015Xiao and Duan, 2016), with remote impacts both downstream (e.g. Zhang et al, 2004;Xue et al, 2018) and upstream (Lu et al, 2017). In autumn or winter, snow anomalies over the TP have been linked to wave trains extending downstream over East Asia and the Pacific (Liu et al, 2017;Li et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

et al. 2019

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Abstract. The Tibetan Plateau (TP) region, often referred to as the Third Pole, is the world's highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impact on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric reanalyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global reanalyses with satellite and in situ data. Yet, snow in reanalyses provides critical surface information for forecast systems from the medium to sub-seasonal timescales. Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, the Japanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), are inter-compared over the TP region. The reanalyses are evaluated against a set of 33 in situ station observations, as well as against the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in situ observations provides confidence in the station data despite the relative paucity of in situ measurement sites and the harsh operating conditions. While several reanalyses show a systematic overestimation of the snow depth or snow cover, the reanalyses that assimilate local in situ observations or IMS snow cover are better capable of representing the shallow, transient snowpack over the TP region. The latter point is clearly demonstrated by examining the family of reanalyses from the ECMWF, of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. We further tested the sensitivity of the ERA5-Land model in offline experiments, assessing the impact of blown snow sublimation, snow cover to snow depth conversion and, more importantly, excessive snowfall. These results suggest that excessive snowfall might be the primary factor for the large overestimation of snow depth and cover in ERA5 reanalysis. Pending a solution for this common model precipitation bias over the Himalayas and the TP, future snow reanalyses that optimally combine the use of satellite snow cover and in situ snow depth observations in the assimilation and analysis cycles have the potential to improve medium-range to sub-seasonal forecasts for water resources applications.

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Section: Introductionmentioning

confidence: 99%

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

et al. 2019

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“…e thermal forcing of the Tibetan Plateau (TP) also plays a decisive role through air pumping [26][27][28]. Moreover, the TP also has a considerable influence on the boreal circulation and precipitation as a significant surface and atmospheric heating source in summer [29,30], which, therefore, is also considered.…”

Section: Introductionmentioning

confidence: 99%

Synergy Effects of the Indian Summer Monsoon and the Tibetan Plateau Heating on Summer Rainfall over North China

Zhao

Zhang

2020

Advances in Meteorology

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An analysis based on July-August precipitation reveals that there is a tripole pattern of the precipitation distribution, that is, significantly increased rainfall over North China (NC) is related to the increased rainfall over the Indian subcontinent (IS) and the decreased rainfall over the southeastern Tibetan Plateau (TP) and vice versa, that corresponds to the Indian summer monsoon (ISM) and TP heating pattern, which are interactive. Therefore, it is necessary to investigate the effect of NC rainfall-related atmospheric circulation and the physical linkage with the two thermal forcings together. The linear baroclinic model (LBM) is applied to determine the dynamics of the process. The results show that an enhanced ISM is accompanied by reduced TP heating, favors convection and easterly anomaly over the IS, and produces a Gill-type Rossby wave that affects the vorticity over North Africa. Meanwhile, there is another Rossby wave originating in North Africa and moving eastward to the Pacific Ocean, which interferes with circulation at mid- to high-latitudes, i.e., it strengthens the cyclone over the Baikal region and stretches the western Pacific subtropical high (WPSH) northward to northeastern Asia, and results in abundant water vapor transported to NC. Furthermore, the strong convection over the IS excites the Kelvin waves over the equatorial region, which moves eastward and generates anticyclones over Philippines, consequently leading to the Pacific-Japan (PJ) pattern. The PJ pattern cooperates with the wave train at midlatitudes, resulting in abundant water vapor being transported to NC. The summer rainfall over NC is therefore modulated by synergistic effect of both the ISM and TP heating.

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“…Due to its spatial extent, elevation and geographical position in the mid-latitudes, it exerts a considerable influence on regional and global climate. The formation and variability of the Asian summer monsoon in particular, is affected by the TP through thermal and mechanical effects (Wu et al, 2012(Wu et al, , 2015Xiao and Duan, 2016), with remote impacts both downstream (e.g., Zhang et al, 2004;Xue et al, 2018) and upstream ( Lu et al, 2017). In autumn or winter, snow anomalies over the TP have also been linked to wave trains extending downstream over East Asia and the Pacific (Liu et al, 2017;Li et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of snow depth and snow-cover over the Tibetan Plateau in global reanalyses using in-situ and satellite remote sensing observations

Orsolini¹,

Wegmann²,

Dutra³

et al. 2019

Preprint

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Abstract. The Tibetan Plateau (TP) region, often referred to as the Third Pole and, is the world highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impacts on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric re-analyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global re-analyses with satellite and in-situ data. Yet, snow in re-analyses provides critical surface information for forecast systems from the medium to sub-seasonal time scales. Here, snow depth and snow cover from 5 recent global reanalysis products are inter-compared over the TP region, and evaluated against a set of 33 in-situ station observations, as well as against the Interactive Multi-sensor Snow and Ice Mapping System (or IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in-situ observations provides confidence in the station data despite the relative paucity of in-situ measurement sites and the harsh operating conditions. While several re-analyses show a systematic over-estimation of the snow depth or snow cover, the reanalyses that assimilate local in-situ observations or IMS snow-cover are better capable of representing the shallow, transient snowpack over the TP region. The later point is clearly demonstrated by examining the family of re-analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF), of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. One missing process in the re-analyses is the blown snow sublimation, which seems important in the dry, windy and cold conditions of the TP. By incorporating a simple parametrisation of this process in the ECMWF land re-analysis, the positive snow bias is somewhat alleviated. Future snow reanalyses that optimally combine the use of satellite snow cover and in-situ snow-depth observations over the Tibetan Plateau region in the assimilation and analysis cycles, along with improved representation of snow processes, have the potential to substantially improve weather and climate prediction and water resources applications.

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Possible effect of the Tibetan Plateau on the “upstream” climate over West Asia, North Africa, South Europe and the North Atlantic

Cited by 56 publications

References 43 publications

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations

Synergy Effects of the Indian Summer Monsoon and the Tibetan Plateau Heating on Summer Rainfall over North China

Evaluation of snow depth and snow-cover over the Tibetan Plateau in global reanalyses using in-situ and satellite remote sensing observations

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